CLA 2 Presentation
BUS 606 Advanced Statistical Concepts And Business Analytics
Agenda
Introduction
Multiple linear regression is the most appropriate statistical technique in predicting the outcome of a dependent variable at different values (Keith, 2019).
The study assessed the relationship between the cost of constructing an LWR Plant and the three predictor variables S, N, and CT.
We assessed the association between the two-test used to examine the employee performance.
Assumption of Regression Analysis
Multicollinearity
Multicollinearity is the condition where the predictor variables are highly correlated (Alin, 2010).
Correlation Analysis
4
Assumption of Regression Analysis Cont’
Normality test
The normality assumption is not violated after transforming the outcome variable C, using natural log (C) (Shapiro-Wilk = 0.967, p = 0.414).
5
Results and Discussion – Regression Analysis
Use Residual Analysis and R2 to Check Your Model
The R-Squared of 0.232 indicates that the model can explain about 23.2% of ln(C)
The low R-Square indicated that the model does not fit the data well (Brown, 2009).
6
Results and Discussion Cont’
State which Variables are Important in predicting the cost of constructing an LWR plant?
S is a significant contributing factor in predicting ln(C)(p = 0.021), but N and CT have no significant effect in predicting (p > 0.05)
7
Results and Discussion Cont’
State a prediction equation that can be used to predict ln(C).
After dropping N and CT from the model since they do not have a significance effect in predicting ln(C), the prediction equation is given by:
Does adding CT improve R2? If so, by what amount?
Adding CT in the model changes R-Square by 0.001 from 0.232 to 0.234 which is not significant different from zero (p > 0.05).
8
Results and Discussion Cont’ - Correlational Analysis
Evaluate the correlation between the two scores and state if there seems to be any association between the two.
There was a weak positive correlation between the two tests (r = 0.187). This suggested that the two test scores were not correlated.
9
Results and Discussion Cont’
Find the probability of upgrading for each division of the sample by the Bayes’ theorem.
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
= 23/43
10
Results and Discussion Cont’
Find the probability of upgrading for each division of the sample by the naïve version of the Bayes’ theorem
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
= 23/43
11
Results and Discussion Cont’
Compare your results in parts b and c and explain the difference or indifference based on observed probabilities
Naïve version and Bayes theorem have similar probabilities.
We have only one predictor in each sample division
This is because Naïve is a ...
Technical And Business Of EntrepreneurshipDiane Allen
The document discusses technical and business undergraduate students' self-efficacy in entrepreneurship. It finds that business undergraduates may have higher self-efficacy in entrepreneurial endeavors than non-business students, as business students had more opportunities to be involved in business activities. Preliminary analyses were conducted to ensure assumptions of normality, linearity and homoscedasticity were not violated.
Lesson 2 Statistics Benefits, Risks, and MeasurementsAssignmen.docxSHIVA101531
Lesson 2: Statistics: Benefits, Risks, and Measurements
Assignments
· See your Course Syllabus for the reading assignments.
· Work through the Lesson 2 online notes that follow.
· Complete the Practice Questions and Lesson 2 Assignment.
Learning Objectives
Chapters 1 and 3
After successfully completing this lesson, you should be able to:
· Identify the three conditions needed to conduct a proper study.
· Apply the seven pitfalls that can be encountered when asking questions in a survey.
· Distinguish between measurement variables and categorical variables.
· Distinguish between continuous variables and discrete variables for those that are measurement variables.
· Distinguish between validity, reliability, and bias.
Terms to Know
From Chapter 1
· statistics
· population
· sample
· observational study
· experiment
· selection bias
· nonresponse bias
From Chapter 3
· data (variable)
· categorical variables
· measurement variables
· measurement (discrete) variables
· measurement (continuous) variables
· validity
· reliability
· bias
2.1 What is Statistics?
Section 2.1. Chapter 1
Overview
What is statistics? If you think statistics is just another math course with many formulas and lifeless numbers, you are not alone. However, this is a myth that hopefully will be debunked as you work through this course. Statistics is about data. More precisely, statistics is a collection of procedures and principles for gaining and processing information from collected data. Knowing these principles and procedures will help you make intelligent decisions in everyday life when faced with uncertainty. The following examples are meant to illuminate the definition of statistics.
Example 2.1. Angry Women
Who are those angry women? (Streitfield, D., 1988 and Wallis, 1987.) In 1987, Shere Hite published a best-selling book called Women and Love: A Cultural Revolution in Progress. This 7-year research project produced a controversial 922-page publication that summarized the results from a survey that was designed to examine how American women feel about their relationships with men. Hite mailed out 100,000 fifteen-page questionnaires to women who were members of a wide variety of organizations across the U.S. These organizations included church, political, volunteer, senior citizen, and counseling groups, among many others. Questionnaires were actually sent to the leader of each organization. The leader was asked to distribute questionnaires to all members. Each questionnaire contained 127 open-ended questions with many parts and follow-ups. Part of Hite’s directions read as follows: “Feel free to skip around and answer only those questions you choose.” Approximately 4500 questionnaires were returned. Below are a few statements from this 1987 publication.
· 84% of women are not emotionally satisfied with their relationships
· 95% of women reported emotional and psychological harassment from their partners
· 70% of women married 5 years or more are having extramarital ...
Hlt 362 v Enhance teaching-snaptutorial.comrobertleew24
For more classes visit
www.snaptutorial.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
Hlt 362 v Believe Possibilities / snaptutorial.comStokesCope25
This document contains an assignment workbook with exercises on summarizing and interpreting statistics from research studies. It includes exercises on independent and paired t-tests, descriptive statistics like mean, median and mode, normal distributions, and skewness/kurtosis. Discussion questions address topics like random sampling, population characteristics, and how graphics/statistics can misrepresent data. The document provides context and data for learning statistical concepts.
Hlt 362 v Exceptional Education / snaptutorial.comBaileya62
For more classes visit
www.snaptutorial.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total
Example Of Search Strategy
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Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
Hlt 362 v Effective Communication / snaptutorial.comHarrisGeorg26
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
What is the total sample size of this study? What frequency and percentage of the total sample were still employed? Show your calculations and round your answer to the nearest whole percent.
Technical And Business Of EntrepreneurshipDiane Allen
The document discusses technical and business undergraduate students' self-efficacy in entrepreneurship. It finds that business undergraduates may have higher self-efficacy in entrepreneurial endeavors than non-business students, as business students had more opportunities to be involved in business activities. Preliminary analyses were conducted to ensure assumptions of normality, linearity and homoscedasticity were not violated.
Lesson 2 Statistics Benefits, Risks, and MeasurementsAssignmen.docxSHIVA101531
Lesson 2: Statistics: Benefits, Risks, and Measurements
Assignments
· See your Course Syllabus for the reading assignments.
· Work through the Lesson 2 online notes that follow.
· Complete the Practice Questions and Lesson 2 Assignment.
Learning Objectives
Chapters 1 and 3
After successfully completing this lesson, you should be able to:
· Identify the three conditions needed to conduct a proper study.
· Apply the seven pitfalls that can be encountered when asking questions in a survey.
· Distinguish between measurement variables and categorical variables.
· Distinguish between continuous variables and discrete variables for those that are measurement variables.
· Distinguish between validity, reliability, and bias.
Terms to Know
From Chapter 1
· statistics
· population
· sample
· observational study
· experiment
· selection bias
· nonresponse bias
From Chapter 3
· data (variable)
· categorical variables
· measurement variables
· measurement (discrete) variables
· measurement (continuous) variables
· validity
· reliability
· bias
2.1 What is Statistics?
Section 2.1. Chapter 1
Overview
What is statistics? If you think statistics is just another math course with many formulas and lifeless numbers, you are not alone. However, this is a myth that hopefully will be debunked as you work through this course. Statistics is about data. More precisely, statistics is a collection of procedures and principles for gaining and processing information from collected data. Knowing these principles and procedures will help you make intelligent decisions in everyday life when faced with uncertainty. The following examples are meant to illuminate the definition of statistics.
Example 2.1. Angry Women
Who are those angry women? (Streitfield, D., 1988 and Wallis, 1987.) In 1987, Shere Hite published a best-selling book called Women and Love: A Cultural Revolution in Progress. This 7-year research project produced a controversial 922-page publication that summarized the results from a survey that was designed to examine how American women feel about their relationships with men. Hite mailed out 100,000 fifteen-page questionnaires to women who were members of a wide variety of organizations across the U.S. These organizations included church, political, volunteer, senior citizen, and counseling groups, among many others. Questionnaires were actually sent to the leader of each organization. The leader was asked to distribute questionnaires to all members. Each questionnaire contained 127 open-ended questions with many parts and follow-ups. Part of Hite’s directions read as follows: “Feel free to skip around and answer only those questions you choose.” Approximately 4500 questionnaires were returned. Below are a few statements from this 1987 publication.
· 84% of women are not emotionally satisfied with their relationships
· 95% of women reported emotional and psychological harassment from their partners
· 70% of women married 5 years or more are having extramarital ...
Hlt 362 v Enhance teaching-snaptutorial.comrobertleew24
For more classes visit
www.snaptutorial.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
Hlt 362 v Believe Possibilities / snaptutorial.comStokesCope25
This document contains an assignment workbook with exercises on summarizing and interpreting statistics from research studies. It includes exercises on independent and paired t-tests, descriptive statistics like mean, median and mode, normal distributions, and skewness/kurtosis. Discussion questions address topics like random sampling, population characteristics, and how graphics/statistics can misrepresent data. The document provides context and data for learning statistical concepts.
Hlt 362 v Exceptional Education / snaptutorial.comBaileya62
For more classes visit
www.snaptutorial.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total
Example Of Search Strategy
Sampling Methods Essay
What is Stress? Essay
Methodology of Research Essay examples
Pro-Life Essay examples
Essay on My Day
Essay about My Life
Essay about My Core Values
The Power of Language Essay examples
My Reflection Of Art
Customer Service Essay examples
My Definition of Success Essay example
A Love Story Essays
For more classes visit
www.snaptutorial.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
Hlt 362 v Effective Communication / snaptutorial.comHarrisGeorg26
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
What is the total sample size of this study? What frequency and percentage of the total sample were still employed? Show your calculations and round your answer to the nearest whole percent.
For more course tutorials visit
www.tutorialrank.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
What is the total sample size of this study? What frequency and percentage of the total sample were still
There are several statistical tests that can be used to investigate correlations between variables based on the type of data and study design:
- A z-test can compare a sample proportion to a population proportion to see if they are significantly different, as when comparing PKU rates.
- Spearman's rank correlation or Pearson's correlation can measure the strength and direction of relationships between ordinal or interval/ratio variables.
- A t-test can analyze differences between repeated measures before and after an intervention to see if they are statistically significant.
- A chi-square test can determine if there is a relationship between categorical variables, such as student responses on a Likert scale. The appropriate test depends on the data
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Running head DISCUSSION ESSAY1DISCUSSION ESSAY4Di.docxtodd271
Running head: DISCUSSION ESSAY
1
DISCUSSION ESSAY
4
Discussion Essay
Name
Academic Institution
April 1, 2019
Discussion Essay
Social control plays a major role in my own life since it dictates what I should do and what I should not. This element claims a degree of my liberty to make choices since I am compelled to please society or find myself in trouble. By this, I am expected to socialize with a certain class of people or else breaking this norm may leave people feeling disappointed with me. I am also expected to carry myself in accordance with my age or else people will think that I have lost my mind or being childish, while as I may simply be in a mood to let loose and just live my life in a care free way even for a moment, because after all it is my life.
On the other hand, social control helps to shape my life in becoming a responsible youth, and the desire to meet this expectation helps in clearing my perception of matters, which also develops my perspective in relation to what society considers moral or immoral. For example, it shapes my position regarding some activities that I would otherwise consider fun yet in the real sense are criminal in nature. As a young person, I feel energetic and adventurous and fun for me is anything thrilling (Lilly et al., 2011). Presently, there are many activities that a young person can indulge in for a thrilling experience. They could include crazy driving, trying out drugs and other substances, or a weekend getaway spree under no adult supervision, just to mention but a few. However, social control comes in handy and redirects such contemplations through the guiding sense it offers through the wisdom of experienced adults such as my parents, teachers, and other guardians in my life.
The power of social influence from my community has helped to develop a sense of commitment within me to follow our social norms. As such, I would say that I see the effect of Travis Hirschi’s social bond theory, which supposes that delinquency occurs in the absence of, or when social bonds are weak (Hirschi, 2002). However, crime is easily averted when social bonds are strong. As such, in an event of social deviance, the strong association I share with parents and community plays a vital role of dissuading me from indulging in delinquency because I have accepted the social conditions of my social group.
Social conditioning has helped me to become a college student instead of being involved in criminal activity. I come from a family that does not take misbehavior kindly. Getting involved in criminal activity is met with harshness from my parents, my father especially. I remember this time immediately after receiving my college acceptance letter. A new neighbor moved in with their two sons of my age and I was more than thrilled to have them for company. Apparently, both boys were using pot and they introduced me on this rainy Saturday evening (Lilly et al., 2011). My first experience set me out of contro.
How to Write an Argumentative Essay Step By Step - Gudwriter. Sample Essay Outlines - 34+ Examples, Format, Pdf | Examples. Argumentative Essay Outline - 9+ Examples, Format, Pdf | Examples. A Sample Argumentative Essay.
This document discusses different types of research designs used in psychology, including correlational research, quasi-experimental research, and problems to look for in research studies. It provides examples of each type of research design. Correlational research seeks to establish relationships between variables without manipulation. Quasi-experimental research blends correlation and experimental approaches by examining interactions between individual differences and manipulations. Problems to look for include confounds, nonrandom sampling, failure to replicate, and lack of comparison groups.
Learning Outcomes1. Describe correlations and regression a.docxSHIVA101531
Learning Outcomes
1. Describe correlations and regression analyses.
2. Analyze the relationship between correlations and predictions.
Introduction
In contrast to Week Three where statistical tests focusing on differences were introduced, in Week Four, you will explore relationships in statistical tests. Correlations and linear regression techniques will be utilized and results will be evaluated and interpreted. The written assignments in Weeks One, Two, and Three prepared you for analyzing and evaluating research articles. In the written assignment this week, you will focus less on actual research and more on the report writing process.
If you work in a social/behavioral sciences field, you will likely be asked to conduct research (i.e., conduct an experiment or study) and create a report based on your findings. Generally speaking, people who investigate a scientific hypothesis have a responsibility to the scientific community to share those results. This is particularly true when that investigation adds to/or contradicts previous research. The research report outlines each step that was done during the research and summarizes the results and conclusions. The goal is to give the reader enough information so that the methods and results can be accurately evaluated, and the conclusions can be replicated if necessary. Although the research report this week will be based on hypothetical and/or fictitious data, the process of creating a correctly formatted research report with all the necessary components will provide you with important skills as you progress through your degree and as you continue into the world of the social/behavioral sciences.
Required Resources
Required Text
Read from the course text, Statistics for the Behavioral & Social Sciences:
· Chapter 8: Correlation
· Chapter 9: Linear Regression
Recommended Resources
Articles
1. Kirwan, J., Lounsbury, J., Gibson, L. (2010). Self-direction in learning and personality: The Big Five and narrow personality traits in relation to learner self-direction. International Journal of Self-Directed Learning, 7(2), 21-34. Retrieved from http://sdlglobal.com/IJSDL/IJSDL7.2-2010.pdf#page=25
· This is an article about personality, self-directed learning, and scale development and the major traits that may affect them. These include: agreeableness, conscientiousness, emotional stability, and openness. It incorporates correlation and regression procedures with tables that display the statistical results.
2. Stark, P.B. (2013). Chapter 9: Regression. Retrieved from http://www.stat.berkeley.edu/~stark/SticiGui/Text/regression.htm
· This website contains several video lectures and examples of how regression is used.
3. Trochim, W. M. (2006). Correlation. In Research Methods Knowledge Base. Retrieved from http://www.socialresearchmethods.net/kb/statcorr.php
· This website contains many tutorials and tools for statistical analyses and methods used in the social sciences. This pa ...
YOUR WORK WILL BE AUTOMATICALLY CHECKED BY BLACKBOARD SAFEASSIGN. .docxodiliagilby
YOUR WORK WILL BE AUTOMATICALLY CHECKED BY BLACKBOARD SAFEASSIGN. ASSIGNMENTS WITH SIMILARITY RATINGS GREATER THAN 35% WILL NOT BE GRADED.
In your own words and GIVE EXAMPLES. Use business English. Check your spelling and grammar. Each answer should be about one-half page
Chapter One
1. Discuss (with examples) what is an I/O and what is a resource-based business model.
Type answer here:
Chapter Two:
2. What ae the differences between the general environment and the industry environment? Why are these differences important?
Type answer here:
Chapter Three
3. What is Value Chain Analysis? How does it help companies earn above-average returns?
Type answer here:
Chapter Four
4. Explain Cost Leadership and Differentiation strategies. Be sure to name a real-life company that practices each strategy
Type answer here.
Chapter Five
5. What factors contribute to the likelihood of a response to a competitive action?
Type answer here:
Chapter Six:
6. What is corporate-level strategy? what is business-level strategy?
Type answer here.
Chapter Eight:
8. List and explain with examples the five entry modes firms may consider as paths to enter the international markets?
Type answer here
Chapter Nine:
9. What is a strategic alliance? What are the three major types of strategic alliances?
Type answer here
Chapters 10
10-. Discuss what is meant by “agency relationship”? What are some actions that firms can take to align the interests of managerial agents with those of the firm’s shareholders?
Type answer here.
Chapters 11
11-. Compare and contrast strategic and financial controls?
Type answer here.
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Download by: [University of Newcastle, Australia] Date: 28 November 2017, At: 15:34
Psychology, Health & Medicine
ISSN: 1354-8506 (Print) 1465-3966 (Online) Journal homepage: http://www.tandfonline.com/loi/cphm20
Feasibility and effectiveness of psychosocial
resilience training: A pilot study of the READY
program
Nicola W. Burton , Ken I. Pakenham & Wendy J. Brown
To cite this article: Nicola W. Burton , Ken I. Pakenham & Wendy J. Brown (2010) Feasibility and
effectiveness of psychosocial resilience training: A pilot study of the READY program, Psychology,
Health & Medicine, 15:3, 266-277, DOI: 10.1080/13548501003758710
To link to this article: https://doi.org/10.1080/13548501003758710
Published online: 17 May 2010.
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Essay On First Day At School. First Day of School - GCSE English - Marked by ...Felicia Gonzales
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Discussion - Week 7Top of FormDiscussion Psychological AspeVinaOconner450
Discussion - Week 7
Top of Form
Discussion: Psychological Aspects of Aging
What does it mean to age “successfully”? Though the concept of success is relative, theories of successful aging explain factors that support individuals as they grow old. Factors such as maintaining physical and mental activity and disengaging from community obligations contribute to older adults’ ability to function. As a social worker, you must understand these supportive factors in order to address the needs of older clients and their families.
As you will see in this week’s media, situations involving Alzheimer’s or dementia, interpersonal conflict, and grief can complicate the process of successful aging. For this Discussion, you review one of two case studies involving an older woman and apply a theory of successful aging to the case.
To Prepare:
· Review the Learning Resources on psychological aspects of later adulthood, focusing on key life events and on theories of successful aging.
· Access the Social Work Case Studies media and explore the cases of Sara and of Francine.
· Select a theory of successful aging to apply to either Sara's or Francine’s case.
By 01/12/2021Post a Discussion in which you:
· Identify whether you have chosen to analyze Sara's or Francine's case for the Discussion.
· Explain key life events that have influenced Sara's or Francine’s psychological functioning. Be sure to substantiate what makes them key in your perspective.
· Explain how you as a social worker might apply a theory of successful aging to Sara’s or Francine’s case. Be sure to provide support for your strategy.
Bottom of Form
Required Readings
Zastrow, C. H., Kirst-Ashman, K. K., & Hessenauer, S. L. (2019). Understanding human behavior and the social environment (11th ed.). Cengage Learning.
· Chapter 15, "Psychological Aspects of Later Adulthood" (pp. 672–702)
Newell, J. M. (2019). An ecological systems framework for professional resilience in social work practice. Social Work, 65(1), 65–73. https://doi.org/10.1093/sw/swz044
Teater, B., & Chonody, J. M. (2020). How do older adults define successful aging? A scoping review. International Journal of Aging and Human Development, 91(4), 599–625. https://doi.org/10.1177/0091415019871207
Yousuf-Abramson, S. (2020). Worden’s tasks of mourning through a social work lens. Journal of Social Work Practice, 1–13. https://doi.org/10.1080/02650533.2020.1843146
Required MediaRequired Readings
Zastrow, C. H., Kirst-Ashman, K. K., & Hessenauer, S. L. (2019). Understanding human behavior and the social environment (11th ed.). Cengage Learning.
· Chapter 15, "Psychological Aspects of Later Adulthood" (pp. 672–702)
Chapter 15 Summary
The following summarizes this chapter’s content as it relates to the learning objectives presented at the beginning of the chapter. Chapter content will help prepare students to
LO 1 Describe the developmental tasks of later adulthood.
Older adults must make a number of developmental psychological ad ...
1. The document discusses a research assignment requiring students to identify a research question from Week 1 that is suitable for a correlational study using correlation or regression analysis.
2. One example research question is "How does employees' motivation affect organizational productivity?", with motivation factors and productivity as variables that could be measured on an ordinal scale.
3. The document provides 10 total example research questions, describes their variables, and discusses appropriate measurement scales for analysis. It also lists required and recommended resources on research methods, correlation, and regression.
Family, Culture, & Career
Week 2
Highs & Lows
Can omit if you would like, but I think my students liked this last quarter!
Weekly Poll
Today’s Agenda
Discussion: Genogram Trends
Culture & Social Context
Psychology of Working
Upcoming Deadlines
Assessment Introduction
Genogram Reflection Paper
What is “Culture”?
Set of guidelines that people inherit from their social environments
that guide how they view the world, respond to it, and behave
in it.
Not synonymous with race, ethnicity, social class, or
immigration status
Impacts us continuously, whether we are aware of it or not
Fluid and changes as cultures and individuals interact
Transmitted across generations
Privilege exists within cultures
and most career theories do not adequately address it…
Bronfenbrenner’s Ecological Model: Exploration of Identity & Social Context
Interaction between your own identities, social location and agency, specific life events and circumstances, and upbringing
Family can provide important context
Don’t exist in isolation - impacted by external things/systems.
E.g., Fish metaphor (you are the fish, what is the fish bowl you are living in?) - zooming out
Breakout Rooms
(next slide)
Genogram Trends
Small Group Discussion
What did you notice?
What are the trends?
How do you want to follow these patterns or chart a new part?
Multiple Identities
We all have multiple identities that shape us and our daily experiences.
Some identities may offer us advantages, and others may offer us disadvantages
Assumptions about us based on these identities will be made, and these assumptions also impact us.
Having awareness of your identities and how they impact you as a person is important, for yourself as a person and your career.
Identities can be formed by culture but culture can also be formed by identity.
Model of Multiple Dimensions of Identity
Based on Social Identities
“portion of an individual's self-concept derived from perceived membership in a relevant social group”
(Jones & MkEwen, 2000)
“portion of an individual's self-concept derived from perceived membership in a relevant social group”
Model of Multiple Dimensions of Identity (cont.)
(Jones & MkEwen, 2000)
Start with your core
Which is most salient to you?
(gets an atom near the core)
What is least salient?
(gets a point farther away from the core)
What, if any, salient identities do not appear on this chart?
What do you notice about the identities that are closer to your core?
Reactions?
How might our identities impact our career choices and interests?
How might others’ assumptions and beliefs about us based on our identities impact our career and interests?
Your Social Context
We all have unique identities which, as we’ve discussed, impact our lives and our career choices, but what about your upbringing and social context growing up?
Some of our identities may give us hints, but it is also important to think about:
opportunities ...
To start everything in this bag means the world to me. I have TakishaPeck109
To start everything in this bag means the world to me. I have 5 items: My TCU Community
Scholar Program certificate, kenya bracelet, PS5 controller, Camera, last but not least an image
of me and Bae Reh.
● TCU Community Scholars is a program that offers a full-ride to student leaders
from 13 majority-minority Dallas-Fort Worth high schools. Their four-year
scholarship includes a supportive residential experience and opportunities to
study abroad. I was given this gift from God through a rigorous process. That
included 2 essays one for admission another one for the community scholar
program. Not to mention 3 interviews after that having to wait for 3 whole months
of anticipation. To know whether I got it or not. This took a great deal of
perseverance and consistency. But I’ll say the true beauty of it is that I learned
alot about myself and what my ambitions/goals are in life. For instance For the
longest time, I have always dreamt of making a significant impact in my
community. Values such as love and concern for other people have always been
my driving force in life. I have always believed that the world has an endless
string of possibilities if only we were bold enough to explore. The Community
Scholar program at TCU will be one such possibility. It will be a golden chance to
enhance my entrepreneurial skills and, in the long run, use them to change the
business culture in my community. The fact that TCU hosts students from
different walks of life will be a good thing for my exposure. I deliberately plan to
share from the perspectives of students from other parts of the world and, in the
process, broaden my understanding of different aspects of business and life in
general. I will then carry my knowledge and experience back to the community
with the hope of convincing them that there is always a different way of doing and
managing a business. I hope to improve the entrepreneurial capacity within my
community. People will be better at running their businesses, and naturally the
living standards will improve.
● My kenya bracelets have huge values in life. It is a constant reminder of where I come
from and the struggles of getting to america. I wasn't like your average child for the most
part of my life. I have been exposed to discrimination and oppression for who I am as
Somali Bantu. I was born in Kenya, but my family immigrated to the United States in
august 2004. At that time, I was three years old, but I'll admit that it is challenging to be a
Somali Bantu in any part of the world due to lifestyle differences. I consider living in the
United States as a clear blessing. Most importantly, my grandmother gave it to me when I
was a kid before she passed. When I wear the bracelet I can feel her presence like she is
standing right next to me.
● I am a huge gamer. I grew up playing games at a young age. The PS5 controller
symbolizes my love for the game that I always come back to at the end of the day. When
I feel like I need to escape the ...
Running Head RESEARCH QUESTION, THESIS, AND OUTLINE1RESEARCH .docxtodd521
The annotated bibliography provides summaries and descriptions of how 9 credible sources will be used to support an argumentative essay on the topic of grass-fed versus grain-fed beef. The sources include books, peer-reviewed articles, magazines, newspapers and websites. The annotations demonstrate that the sources are relevant and will help build the argument that grass-fed beef is better for health, environment and animal welfare compared to grain-fed beef. Reflection questions are answered thoroughly and demonstrate search strategies and difficulties finding sources.
Learning SimulationSpecific information to consider for your desig.docxVinaOconner450
Learning Simulation
Specific information to consider for your design blueprint (You may use this information as content for your Web site.)
Background Information
Canterbury Village University is a small liberal arts college in South West Ohio, accredited by the Mid-West Commission on Higher Education, and dedicated to the education of students to think and act critically, creatively, and ethically as professionals and scholars.
The Alumni Association furthers the principal objectives of the University by supporting the legacy of the founders and alumni, and fostering ongoing active relationships among graduates, current students, members of the faculty, and friends of the University.
The Alumni GOLD (Graduates Of the Last Decade) Leadership Congress is established to secure and increase the lifelong involvement of graduates of the past decade in the mission of the University through volunteer, philanthropic, social, and career networking activities.
As this group represents one-third of the alumni population, they are a unique and vital constituency of the University, and the Association.
Website Goal
This website will is designed to recruit recent graduates to become members of the Alumni Association. And become involved in alumni activities.
Website Objectives
After viewing this site, the graduates will be able to:
Decide whether to join the Alumni Association.
Pledge and donate financial support to the University.
Volunteer to serve on various alumni committees.
Register to attend events at the University, especially Alumni Weekend.
The Target Audience
Recent graduates (last 10 years) of the University who have not yet joined the Alumni Association
Approximately 21-32 years old
Male and female
Culturally and socio-economically diverse
Working primarily in professional, community service, business, and family related endeavors, or are in graduate school, the military, or volunteer service
Are relatively new to the workforce
Have a strong sense of loyalty to their alma mater and their communities because of the University mission and their education
The web site will comprise several pages to include but not be limited to:
A Home Page (Cover)
with some content, and the following menu with links: [a link to this page should be available on every page]
About the University
About the Office of Alumni Relations
About the Alumni Association
You will then create additional pages and links for Item 3, Alumni Relations to include but not be limited to:
Mission Statement of the Alumni Association
Goal and Objectives
Contact Information
Application Information
Profile Update
Donation Information
Mentor Program
Events Calendar
Flowchart – Site Map - Blueprint
Below is a very simple template. It serves as a Site Map, a visual representation of your blueprint to help you focus and form your website. (This is one possible solution, however, it is not complete, you have more to build with the information provided.)
Example of a Flowchart Diagram
Two exam.
Learning Activity 1Identify key external forces Then interview.docxVinaOconner450
Learning Activity 1:
Identify key external forces? Then interview--in person, by phone or whatever means practical--a former or current employer/boss about
one
(1) force that critically concerns the organization and explain it in a practical manner vis-a-vis opportunity and/or threats.
Note: Please ensure to properly cite your interview IAW APA guidance.
Learning Activity 2:
Explain the implications, effects or consequences of at least one of Porter's Five Forces on an organization?
.
Learning ReflectionHow would you apply the four p’s to a service .docxVinaOconner450
Learning Reflection
How would you apply the four p’s to a service? Choose a service you use. What is the service? What is the name of the business that delivers the service? Describe the role of the four P’s in the company’s marketing for that service.
APA Formatting Not Needed
.
Learning Activity #1Please discuss the ethical lessons that you le.docxVinaOconner450
This document outlines two learning activities. The first asks students to discuss ethical lessons learned in class that will help them in the future, and to discuss ethics in the workplace. The second activity asks students to research a company known for strong corporate ethics, and discuss why it is considered a good example of ethical leadership and how it applies ethical theories.
Learning Activity Data on Child AbuseChildren are suffering from .docxVinaOconner450
Learning Activity: Data on Child Abuse
Children are suffering from a hidden epidemic of child abuse and neglect.
Create a 5–10 slide presentation in PowerPoint® that provides at least three statistical data points that you consider critical to increase society’s awareness about the serious issues related to child abuse. One of the data points should be from your residential state. The others can be national statistics. Include why knowing this information is important.
The statistical data should come from at least three (3) different, credible sources, and cannot be more than 3-years-old.
The presentation should include a title slide and reference slide (in addition to the 5–10 slides of content). The data source, including date must be clearly identified with each statistical data point.
Your slides should have large legible font size and appropriate color use. Consider including other enhancements such as photos, charts, graphs, etc.
Automatic or timed transitions of slides are not required.
.
Learning Activity #1Joe Jackson owned a sawmill in Stuttgart, Arka.docxVinaOconner450
Learning Activity #1
Joe Jackson owned a sawmill in Stuttgart, Arkansas. It was a family business that had not changed in 50 years. Having grown up in the business, Joe had never really investigated the strengths and weaknesses of his position as Vice President. His father was always the President and he and his older brother Jacob were the heirs. The business was in turmoil because his father’s health was precarious and he was forced to step down. Joe’s brother was expecting to step up to the role of Vice President but Joe knew that was a mistake. The business itself was being quickly eroded because of the sustainability issues facing the world. Joe could see this but not Jacob. Joe needed to have a long talk with Jacob to make him see reason. Either they worked together for the future or Joe would have to take the lead role.
TASK:
Prepare an outline of points for Joe to make in his discussion with his brother. Explain the role of the 21
st
century leader and why it differs from that of the 20
th
century leader. Make sure to reference your reading material to validate the points you make.
L
earning Activity 2:
John Kotter in his article “
What
Leaders Really D
o
" makes the following statement: Managers promote stability while Leaders press for change, and only organizations that embrace both sides of the contradiction can thrive in turbulent times."
TASK:
After reading the background information below, explain what you think Dean Adams’ role should be in light of this quote; the leaders or the manager’s? Identify the two roles leader and manager. Be sure to include in your comments the different solutions that may result from a leader's perspective and that of the manager's perspective as well as where they overlap. Finally, suggest which role’s perspective is best for Adam and the organization and why.
Background: Studer International
At 7:30
a.m.,
Dean Adams hit the snooze alarm for the third time, but he knew he could never go back to sleep. Rubbing his eyes and shaking off a headache, Adams first checked his BlackBerry and read an urgent message from his boss, explaining that Sue Chan, chief security analyst, had resigned this morning and needed to be replaced immediately. Frustrated, Adams lumbered toward the shower, hoping it would energize him to face another day. After last night’s management meeting, which had ended after midnight, he was reeling from the news that his Wall Street employer, Studer International, was spiraling toward a financial meltdown.
Adams scratched his head and wondered, “How could one of the world’s largest insurance companies plummet from being the gold standard in the industry to one struggling for survival?” At the end of 2007, Studer had $100 billion in annual revenues, 65 million customers, and 96,000 employees in 130 countries. One year later and staggered by losses stemming from the credit crisis, Studer teetered on the brink of failure and was in need of emergency government assistance. .
Learning ModulesCh. 11 Corrections History and Institutions His.docxVinaOconner450
Learning Modules
Ch. 11: Corrections History and Institutions > History of Prisons
Ch. 11: Corrections History and Institutions > Correctional System
Myths & Issues Videos
Ch. 11: Corrections History and Institutions > Myth v. Reality: The Correctional System Rehabilitates Offenders
Write
a 750 words paper using the information found in the CJi Interactive Multimedia and this week’s readings. Include the following in your paper:
An explanation of factors influencing growth in jails, state prisons, and federal prisons
Conclusion
Format
your paper consistent with APA guidelines.
** No Plagiarism ** also most of the info is on chapter 11
.
Learning goal To develop your ability to systematically analyze and.docxVinaOconner450
The document provides instructions for a strategic analysis and plan for Uber. Students are to take on the role of Uber's top management team and prepare a 3 page, double spaced paper analyzing Uber's current capabilities using a DEI framework, current customers, competitors and complementors. The paper should then propose capabilities and expected changes to customers, competitors and complementors for a specified future time frame along with rationales and major implementation issues.
More Related Content
Similar to CLA 2 PresentationBUS 606 Advanced Statistical Concepts An
For more course tutorials visit
www.tutorialrank.com
Exercise 6
What are the frequency and percentage of the COPD patients in the severe airflow limitation group who are employed in the Eckerblad et al. (2014) study?
What percentage of the total sample is retired? What percentage of the total sample is on sick leave?
What is the total sample size of this study? What frequency and percentage of the total sample were still
There are several statistical tests that can be used to investigate correlations between variables based on the type of data and study design:
- A z-test can compare a sample proportion to a population proportion to see if they are significantly different, as when comparing PKU rates.
- Spearman's rank correlation or Pearson's correlation can measure the strength and direction of relationships between ordinal or interval/ratio variables.
- A t-test can analyze differences between repeated measures before and after an intervention to see if they are statistically significant.
- A chi-square test can determine if there is a relationship between categorical variables, such as student responses on a Likert scale. The appropriate test depends on the data
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Running head DISCUSSION ESSAY1DISCUSSION ESSAY4Di.docxtodd271
Running head: DISCUSSION ESSAY
1
DISCUSSION ESSAY
4
Discussion Essay
Name
Academic Institution
April 1, 2019
Discussion Essay
Social control plays a major role in my own life since it dictates what I should do and what I should not. This element claims a degree of my liberty to make choices since I am compelled to please society or find myself in trouble. By this, I am expected to socialize with a certain class of people or else breaking this norm may leave people feeling disappointed with me. I am also expected to carry myself in accordance with my age or else people will think that I have lost my mind or being childish, while as I may simply be in a mood to let loose and just live my life in a care free way even for a moment, because after all it is my life.
On the other hand, social control helps to shape my life in becoming a responsible youth, and the desire to meet this expectation helps in clearing my perception of matters, which also develops my perspective in relation to what society considers moral or immoral. For example, it shapes my position regarding some activities that I would otherwise consider fun yet in the real sense are criminal in nature. As a young person, I feel energetic and adventurous and fun for me is anything thrilling (Lilly et al., 2011). Presently, there are many activities that a young person can indulge in for a thrilling experience. They could include crazy driving, trying out drugs and other substances, or a weekend getaway spree under no adult supervision, just to mention but a few. However, social control comes in handy and redirects such contemplations through the guiding sense it offers through the wisdom of experienced adults such as my parents, teachers, and other guardians in my life.
The power of social influence from my community has helped to develop a sense of commitment within me to follow our social norms. As such, I would say that I see the effect of Travis Hirschi’s social bond theory, which supposes that delinquency occurs in the absence of, or when social bonds are weak (Hirschi, 2002). However, crime is easily averted when social bonds are strong. As such, in an event of social deviance, the strong association I share with parents and community plays a vital role of dissuading me from indulging in delinquency because I have accepted the social conditions of my social group.
Social conditioning has helped me to become a college student instead of being involved in criminal activity. I come from a family that does not take misbehavior kindly. Getting involved in criminal activity is met with harshness from my parents, my father especially. I remember this time immediately after receiving my college acceptance letter. A new neighbor moved in with their two sons of my age and I was more than thrilled to have them for company. Apparently, both boys were using pot and they introduced me on this rainy Saturday evening (Lilly et al., 2011). My first experience set me out of contro.
How to Write an Argumentative Essay Step By Step - Gudwriter. Sample Essay Outlines - 34+ Examples, Format, Pdf | Examples. Argumentative Essay Outline - 9+ Examples, Format, Pdf | Examples. A Sample Argumentative Essay.
This document discusses different types of research designs used in psychology, including correlational research, quasi-experimental research, and problems to look for in research studies. It provides examples of each type of research design. Correlational research seeks to establish relationships between variables without manipulation. Quasi-experimental research blends correlation and experimental approaches by examining interactions between individual differences and manipulations. Problems to look for include confounds, nonrandom sampling, failure to replicate, and lack of comparison groups.
Learning Outcomes1. Describe correlations and regression a.docxSHIVA101531
Learning Outcomes
1. Describe correlations and regression analyses.
2. Analyze the relationship between correlations and predictions.
Introduction
In contrast to Week Three where statistical tests focusing on differences were introduced, in Week Four, you will explore relationships in statistical tests. Correlations and linear regression techniques will be utilized and results will be evaluated and interpreted. The written assignments in Weeks One, Two, and Three prepared you for analyzing and evaluating research articles. In the written assignment this week, you will focus less on actual research and more on the report writing process.
If you work in a social/behavioral sciences field, you will likely be asked to conduct research (i.e., conduct an experiment or study) and create a report based on your findings. Generally speaking, people who investigate a scientific hypothesis have a responsibility to the scientific community to share those results. This is particularly true when that investigation adds to/or contradicts previous research. The research report outlines each step that was done during the research and summarizes the results and conclusions. The goal is to give the reader enough information so that the methods and results can be accurately evaluated, and the conclusions can be replicated if necessary. Although the research report this week will be based on hypothetical and/or fictitious data, the process of creating a correctly formatted research report with all the necessary components will provide you with important skills as you progress through your degree and as you continue into the world of the social/behavioral sciences.
Required Resources
Required Text
Read from the course text, Statistics for the Behavioral & Social Sciences:
· Chapter 8: Correlation
· Chapter 9: Linear Regression
Recommended Resources
Articles
1. Kirwan, J., Lounsbury, J., Gibson, L. (2010). Self-direction in learning and personality: The Big Five and narrow personality traits in relation to learner self-direction. International Journal of Self-Directed Learning, 7(2), 21-34. Retrieved from http://sdlglobal.com/IJSDL/IJSDL7.2-2010.pdf#page=25
· This is an article about personality, self-directed learning, and scale development and the major traits that may affect them. These include: agreeableness, conscientiousness, emotional stability, and openness. It incorporates correlation and regression procedures with tables that display the statistical results.
2. Stark, P.B. (2013). Chapter 9: Regression. Retrieved from http://www.stat.berkeley.edu/~stark/SticiGui/Text/regression.htm
· This website contains several video lectures and examples of how regression is used.
3. Trochim, W. M. (2006). Correlation. In Research Methods Knowledge Base. Retrieved from http://www.socialresearchmethods.net/kb/statcorr.php
· This website contains many tutorials and tools for statistical analyses and methods used in the social sciences. This pa ...
YOUR WORK WILL BE AUTOMATICALLY CHECKED BY BLACKBOARD SAFEASSIGN. .docxodiliagilby
YOUR WORK WILL BE AUTOMATICALLY CHECKED BY BLACKBOARD SAFEASSIGN. ASSIGNMENTS WITH SIMILARITY RATINGS GREATER THAN 35% WILL NOT BE GRADED.
In your own words and GIVE EXAMPLES. Use business English. Check your spelling and grammar. Each answer should be about one-half page
Chapter One
1. Discuss (with examples) what is an I/O and what is a resource-based business model.
Type answer here:
Chapter Two:
2. What ae the differences between the general environment and the industry environment? Why are these differences important?
Type answer here:
Chapter Three
3. What is Value Chain Analysis? How does it help companies earn above-average returns?
Type answer here:
Chapter Four
4. Explain Cost Leadership and Differentiation strategies. Be sure to name a real-life company that practices each strategy
Type answer here.
Chapter Five
5. What factors contribute to the likelihood of a response to a competitive action?
Type answer here:
Chapter Six:
6. What is corporate-level strategy? what is business-level strategy?
Type answer here.
Chapter Eight:
8. List and explain with examples the five entry modes firms may consider as paths to enter the international markets?
Type answer here
Chapter Nine:
9. What is a strategic alliance? What are the three major types of strategic alliances?
Type answer here
Chapters 10
10-. Discuss what is meant by “agency relationship”? What are some actions that firms can take to align the interests of managerial agents with those of the firm’s shareholders?
Type answer here.
Chapters 11
11-. Compare and contrast strategic and financial controls?
Type answer here.
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=cphm20
Download by: [University of Newcastle, Australia] Date: 28 November 2017, At: 15:34
Psychology, Health & Medicine
ISSN: 1354-8506 (Print) 1465-3966 (Online) Journal homepage: http://www.tandfonline.com/loi/cphm20
Feasibility and effectiveness of psychosocial
resilience training: A pilot study of the READY
program
Nicola W. Burton , Ken I. Pakenham & Wendy J. Brown
To cite this article: Nicola W. Burton , Ken I. Pakenham & Wendy J. Brown (2010) Feasibility and
effectiveness of psychosocial resilience training: A pilot study of the READY program, Psychology,
Health & Medicine, 15:3, 266-277, DOI: 10.1080/13548501003758710
To link to this article: https://doi.org/10.1080/13548501003758710
Published online: 17 May 2010.
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Essay On First Day At School. First Day of School - GCSE English - Marked by ...Felicia Gonzales
Essay About My First Day at a New School Free Essay Example. My first day at a new school Free Essay Example. My First Day At School Short Essay In English - School Walls. Write an Essay on My First Day in School PDF - English Compositions. The First Day of School Tutoring Perth Little Learning Planet .... First Day of High School Essay - 150 Words: Essay Example, 168 words .... 015 Essay Example First Day Of School Thatsnotus. My First Day At School Essay-For all level students Ontaheen. My First Day in School Essay Essay on My First Day in School for .... My first day at a new school narrative essay. My First Day At School .... First Day of School - GCSE English - Marked by Teachers.com. My first day in high school essay. Essay On My First Day At School For Class 8 - School Walls. Writing about my first day at secondary school. My First Day At School English Essay - EASY MCQS QUIZ TEST. Write An Essay My First Day At School Login Required. Write a narrative essay about your first day in school Abilene - how to .... my first day at school essay write essay on my first day at school .... Esse for You: A narrative essay about my first day at school. My First Day At School Paragraph For Class 9 - School Walls. 016 Essay Example First Day Of School Thatsnotus. First day of school experience essay. Personal Narrative Essay: My .... First day of school essay - frudgereport294.web.fc2.com. My First Day At School Short Essay in English For Students - Mirage .... My first day at school essay My first day at school english essay .... write an essay my first day at school. First day at a new school essay. First Day of School Free Essay Example. First Day At School Essay Telegraph. First Day Of High School Essay Essay About First Day of Secondary .... My First Day In School Essay : Essay on My First Day In School in .... College Essay: First day at school short paragraph Essay On First Day At School Essay On First Day At School. First Day of School - GCSE English - Marked by Teachers.com
Discussion - Week 7Top of FormDiscussion Psychological AspeVinaOconner450
Discussion - Week 7
Top of Form
Discussion: Psychological Aspects of Aging
What does it mean to age “successfully”? Though the concept of success is relative, theories of successful aging explain factors that support individuals as they grow old. Factors such as maintaining physical and mental activity and disengaging from community obligations contribute to older adults’ ability to function. As a social worker, you must understand these supportive factors in order to address the needs of older clients and their families.
As you will see in this week’s media, situations involving Alzheimer’s or dementia, interpersonal conflict, and grief can complicate the process of successful aging. For this Discussion, you review one of two case studies involving an older woman and apply a theory of successful aging to the case.
To Prepare:
· Review the Learning Resources on psychological aspects of later adulthood, focusing on key life events and on theories of successful aging.
· Access the Social Work Case Studies media and explore the cases of Sara and of Francine.
· Select a theory of successful aging to apply to either Sara's or Francine’s case.
By 01/12/2021Post a Discussion in which you:
· Identify whether you have chosen to analyze Sara's or Francine's case for the Discussion.
· Explain key life events that have influenced Sara's or Francine’s psychological functioning. Be sure to substantiate what makes them key in your perspective.
· Explain how you as a social worker might apply a theory of successful aging to Sara’s or Francine’s case. Be sure to provide support for your strategy.
Bottom of Form
Required Readings
Zastrow, C. H., Kirst-Ashman, K. K., & Hessenauer, S. L. (2019). Understanding human behavior and the social environment (11th ed.). Cengage Learning.
· Chapter 15, "Psychological Aspects of Later Adulthood" (pp. 672–702)
Newell, J. M. (2019). An ecological systems framework for professional resilience in social work practice. Social Work, 65(1), 65–73. https://doi.org/10.1093/sw/swz044
Teater, B., & Chonody, J. M. (2020). How do older adults define successful aging? A scoping review. International Journal of Aging and Human Development, 91(4), 599–625. https://doi.org/10.1177/0091415019871207
Yousuf-Abramson, S. (2020). Worden’s tasks of mourning through a social work lens. Journal of Social Work Practice, 1–13. https://doi.org/10.1080/02650533.2020.1843146
Required MediaRequired Readings
Zastrow, C. H., Kirst-Ashman, K. K., & Hessenauer, S. L. (2019). Understanding human behavior and the social environment (11th ed.). Cengage Learning.
· Chapter 15, "Psychological Aspects of Later Adulthood" (pp. 672–702)
Chapter 15 Summary
The following summarizes this chapter’s content as it relates to the learning objectives presented at the beginning of the chapter. Chapter content will help prepare students to
LO 1 Describe the developmental tasks of later adulthood.
Older adults must make a number of developmental psychological ad ...
1. The document discusses a research assignment requiring students to identify a research question from Week 1 that is suitable for a correlational study using correlation or regression analysis.
2. One example research question is "How does employees' motivation affect organizational productivity?", with motivation factors and productivity as variables that could be measured on an ordinal scale.
3. The document provides 10 total example research questions, describes their variables, and discusses appropriate measurement scales for analysis. It also lists required and recommended resources on research methods, correlation, and regression.
Family, Culture, & Career
Week 2
Highs & Lows
Can omit if you would like, but I think my students liked this last quarter!
Weekly Poll
Today’s Agenda
Discussion: Genogram Trends
Culture & Social Context
Psychology of Working
Upcoming Deadlines
Assessment Introduction
Genogram Reflection Paper
What is “Culture”?
Set of guidelines that people inherit from their social environments
that guide how they view the world, respond to it, and behave
in it.
Not synonymous with race, ethnicity, social class, or
immigration status
Impacts us continuously, whether we are aware of it or not
Fluid and changes as cultures and individuals interact
Transmitted across generations
Privilege exists within cultures
and most career theories do not adequately address it…
Bronfenbrenner’s Ecological Model: Exploration of Identity & Social Context
Interaction between your own identities, social location and agency, specific life events and circumstances, and upbringing
Family can provide important context
Don’t exist in isolation - impacted by external things/systems.
E.g., Fish metaphor (you are the fish, what is the fish bowl you are living in?) - zooming out
Breakout Rooms
(next slide)
Genogram Trends
Small Group Discussion
What did you notice?
What are the trends?
How do you want to follow these patterns or chart a new part?
Multiple Identities
We all have multiple identities that shape us and our daily experiences.
Some identities may offer us advantages, and others may offer us disadvantages
Assumptions about us based on these identities will be made, and these assumptions also impact us.
Having awareness of your identities and how they impact you as a person is important, for yourself as a person and your career.
Identities can be formed by culture but culture can also be formed by identity.
Model of Multiple Dimensions of Identity
Based on Social Identities
“portion of an individual's self-concept derived from perceived membership in a relevant social group”
(Jones & MkEwen, 2000)
“portion of an individual's self-concept derived from perceived membership in a relevant social group”
Model of Multiple Dimensions of Identity (cont.)
(Jones & MkEwen, 2000)
Start with your core
Which is most salient to you?
(gets an atom near the core)
What is least salient?
(gets a point farther away from the core)
What, if any, salient identities do not appear on this chart?
What do you notice about the identities that are closer to your core?
Reactions?
How might our identities impact our career choices and interests?
How might others’ assumptions and beliefs about us based on our identities impact our career and interests?
Your Social Context
We all have unique identities which, as we’ve discussed, impact our lives and our career choices, but what about your upbringing and social context growing up?
Some of our identities may give us hints, but it is also important to think about:
opportunities ...
To start everything in this bag means the world to me. I have TakishaPeck109
To start everything in this bag means the world to me. I have 5 items: My TCU Community
Scholar Program certificate, kenya bracelet, PS5 controller, Camera, last but not least an image
of me and Bae Reh.
● TCU Community Scholars is a program that offers a full-ride to student leaders
from 13 majority-minority Dallas-Fort Worth high schools. Their four-year
scholarship includes a supportive residential experience and opportunities to
study abroad. I was given this gift from God through a rigorous process. That
included 2 essays one for admission another one for the community scholar
program. Not to mention 3 interviews after that having to wait for 3 whole months
of anticipation. To know whether I got it or not. This took a great deal of
perseverance and consistency. But I’ll say the true beauty of it is that I learned
alot about myself and what my ambitions/goals are in life. For instance For the
longest time, I have always dreamt of making a significant impact in my
community. Values such as love and concern for other people have always been
my driving force in life. I have always believed that the world has an endless
string of possibilities if only we were bold enough to explore. The Community
Scholar program at TCU will be one such possibility. It will be a golden chance to
enhance my entrepreneurial skills and, in the long run, use them to change the
business culture in my community. The fact that TCU hosts students from
different walks of life will be a good thing for my exposure. I deliberately plan to
share from the perspectives of students from other parts of the world and, in the
process, broaden my understanding of different aspects of business and life in
general. I will then carry my knowledge and experience back to the community
with the hope of convincing them that there is always a different way of doing and
managing a business. I hope to improve the entrepreneurial capacity within my
community. People will be better at running their businesses, and naturally the
living standards will improve.
● My kenya bracelets have huge values in life. It is a constant reminder of where I come
from and the struggles of getting to america. I wasn't like your average child for the most
part of my life. I have been exposed to discrimination and oppression for who I am as
Somali Bantu. I was born in Kenya, but my family immigrated to the United States in
august 2004. At that time, I was three years old, but I'll admit that it is challenging to be a
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● I am a huge gamer. I grew up playing games at a young age. The PS5 controller
symbolizes my love for the game that I always come back to at the end of the day. When
I feel like I need to escape the ...
Running Head RESEARCH QUESTION, THESIS, AND OUTLINE1RESEARCH .docxtodd521
The annotated bibliography provides summaries and descriptions of how 9 credible sources will be used to support an argumentative essay on the topic of grass-fed versus grain-fed beef. The sources include books, peer-reviewed articles, magazines, newspapers and websites. The annotations demonstrate that the sources are relevant and will help build the argument that grass-fed beef is better for health, environment and animal welfare compared to grain-fed beef. Reflection questions are answered thoroughly and demonstrate search strategies and difficulties finding sources.
Similar to CLA 2 PresentationBUS 606 Advanced Statistical Concepts An (14)
Learning SimulationSpecific information to consider for your desig.docxVinaOconner450
Learning Simulation
Specific information to consider for your design blueprint (You may use this information as content for your Web site.)
Background Information
Canterbury Village University is a small liberal arts college in South West Ohio, accredited by the Mid-West Commission on Higher Education, and dedicated to the education of students to think and act critically, creatively, and ethically as professionals and scholars.
The Alumni Association furthers the principal objectives of the University by supporting the legacy of the founders and alumni, and fostering ongoing active relationships among graduates, current students, members of the faculty, and friends of the University.
The Alumni GOLD (Graduates Of the Last Decade) Leadership Congress is established to secure and increase the lifelong involvement of graduates of the past decade in the mission of the University through volunteer, philanthropic, social, and career networking activities.
As this group represents one-third of the alumni population, they are a unique and vital constituency of the University, and the Association.
Website Goal
This website will is designed to recruit recent graduates to become members of the Alumni Association. And become involved in alumni activities.
Website Objectives
After viewing this site, the graduates will be able to:
Decide whether to join the Alumni Association.
Pledge and donate financial support to the University.
Volunteer to serve on various alumni committees.
Register to attend events at the University, especially Alumni Weekend.
The Target Audience
Recent graduates (last 10 years) of the University who have not yet joined the Alumni Association
Approximately 21-32 years old
Male and female
Culturally and socio-economically diverse
Working primarily in professional, community service, business, and family related endeavors, or are in graduate school, the military, or volunteer service
Are relatively new to the workforce
Have a strong sense of loyalty to their alma mater and their communities because of the University mission and their education
The web site will comprise several pages to include but not be limited to:
A Home Page (Cover)
with some content, and the following menu with links: [a link to this page should be available on every page]
About the University
About the Office of Alumni Relations
About the Alumni Association
You will then create additional pages and links for Item 3, Alumni Relations to include but not be limited to:
Mission Statement of the Alumni Association
Goal and Objectives
Contact Information
Application Information
Profile Update
Donation Information
Mentor Program
Events Calendar
Flowchart – Site Map - Blueprint
Below is a very simple template. It serves as a Site Map, a visual representation of your blueprint to help you focus and form your website. (This is one possible solution, however, it is not complete, you have more to build with the information provided.)
Example of a Flowchart Diagram
Two exam.
Learning Activity 1Identify key external forces Then interview.docxVinaOconner450
Learning Activity 1:
Identify key external forces? Then interview--in person, by phone or whatever means practical--a former or current employer/boss about
one
(1) force that critically concerns the organization and explain it in a practical manner vis-a-vis opportunity and/or threats.
Note: Please ensure to properly cite your interview IAW APA guidance.
Learning Activity 2:
Explain the implications, effects or consequences of at least one of Porter's Five Forces on an organization?
.
Learning ReflectionHow would you apply the four p’s to a service .docxVinaOconner450
Learning Reflection
How would you apply the four p’s to a service? Choose a service you use. What is the service? What is the name of the business that delivers the service? Describe the role of the four P’s in the company’s marketing for that service.
APA Formatting Not Needed
.
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Learning Activity Data on Child AbuseChildren are suffering from .docxVinaOconner450
Learning Activity: Data on Child Abuse
Children are suffering from a hidden epidemic of child abuse and neglect.
Create a 5–10 slide presentation in PowerPoint® that provides at least three statistical data points that you consider critical to increase society’s awareness about the serious issues related to child abuse. One of the data points should be from your residential state. The others can be national statistics. Include why knowing this information is important.
The statistical data should come from at least three (3) different, credible sources, and cannot be more than 3-years-old.
The presentation should include a title slide and reference slide (in addition to the 5–10 slides of content). The data source, including date must be clearly identified with each statistical data point.
Your slides should have large legible font size and appropriate color use. Consider including other enhancements such as photos, charts, graphs, etc.
Automatic or timed transitions of slides are not required.
.
Learning Activity #1Joe Jackson owned a sawmill in Stuttgart, Arka.docxVinaOconner450
Learning Activity #1
Joe Jackson owned a sawmill in Stuttgart, Arkansas. It was a family business that had not changed in 50 years. Having grown up in the business, Joe had never really investigated the strengths and weaknesses of his position as Vice President. His father was always the President and he and his older brother Jacob were the heirs. The business was in turmoil because his father’s health was precarious and he was forced to step down. Joe’s brother was expecting to step up to the role of Vice President but Joe knew that was a mistake. The business itself was being quickly eroded because of the sustainability issues facing the world. Joe could see this but not Jacob. Joe needed to have a long talk with Jacob to make him see reason. Either they worked together for the future or Joe would have to take the lead role.
TASK:
Prepare an outline of points for Joe to make in his discussion with his brother. Explain the role of the 21
st
century leader and why it differs from that of the 20
th
century leader. Make sure to reference your reading material to validate the points you make.
L
earning Activity 2:
John Kotter in his article “
What
Leaders Really D
o
" makes the following statement: Managers promote stability while Leaders press for change, and only organizations that embrace both sides of the contradiction can thrive in turbulent times."
TASK:
After reading the background information below, explain what you think Dean Adams’ role should be in light of this quote; the leaders or the manager’s? Identify the two roles leader and manager. Be sure to include in your comments the different solutions that may result from a leader's perspective and that of the manager's perspective as well as where they overlap. Finally, suggest which role’s perspective is best for Adam and the organization and why.
Background: Studer International
At 7:30
a.m.,
Dean Adams hit the snooze alarm for the third time, but he knew he could never go back to sleep. Rubbing his eyes and shaking off a headache, Adams first checked his BlackBerry and read an urgent message from his boss, explaining that Sue Chan, chief security analyst, had resigned this morning and needed to be replaced immediately. Frustrated, Adams lumbered toward the shower, hoping it would energize him to face another day. After last night’s management meeting, which had ended after midnight, he was reeling from the news that his Wall Street employer, Studer International, was spiraling toward a financial meltdown.
Adams scratched his head and wondered, “How could one of the world’s largest insurance companies plummet from being the gold standard in the industry to one struggling for survival?” At the end of 2007, Studer had $100 billion in annual revenues, 65 million customers, and 96,000 employees in 130 countries. One year later and staggered by losses stemming from the credit crisis, Studer teetered on the brink of failure and was in need of emergency government assistance. .
Learning ModulesCh. 11 Corrections History and Institutions His.docxVinaOconner450
Learning Modules
Ch. 11: Corrections History and Institutions > History of Prisons
Ch. 11: Corrections History and Institutions > Correctional System
Myths & Issues Videos
Ch. 11: Corrections History and Institutions > Myth v. Reality: The Correctional System Rehabilitates Offenders
Write
a 750 words paper using the information found in the CJi Interactive Multimedia and this week’s readings. Include the following in your paper:
An explanation of factors influencing growth in jails, state prisons, and federal prisons
Conclusion
Format
your paper consistent with APA guidelines.
** No Plagiarism ** also most of the info is on chapter 11
.
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Learning Activity #1
:
What are the theoretical differences between a Small Business and a Global Business. Include a brief discussion and examples of them both. Also state how they contribute or detract from their individual communities in details.
Learning Activity #2
: In detail define what is a business plan and the objectives of developing an effective one. Also share in detail two reasons why a business plan is viewed as a foundational tool in developing a successful business and/or firm.
.
LEADERSHIPImagine you are the HR, describe the role of a leade.docxVinaOconner450
LEADERSHIP
Imagine you are the HR, describe the role of a leader in your business.
Is Everybody’s Business
Write (4) pages paper in which you:
Typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides.
Include a cover page containing the title of the assignment, your name, your professor’s name, the course title, and the date. The cover page is not included in the required page length.
use the attachment
.
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The professor is looking for help analyzing the results of a staff survey by generating frequencies, percentages in a pivot table and compiling a visual result. The survey questions and response codes have been entered. A 250-word APA style analysis and report of the findings is needed.
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.
.
Learning Activity 1Impart your understanding and the organizati.docxVinaOconner450
Learning Activity 1:
Impart your understanding and the organizational implications of the Internal and External Analyses!
Learning Activity 2:
Provide a
numerical
example of a basic/key financial ratio and explain its organizational implications!
Look at attached for help on this and sites below:
http://www.strategicmanagementinsight.com/tools/vrio.html
https://chris264.wordpress.com/2012/09/23/vriovaluerarityimitabilityorganization/
.
Leadership versus Management Rost (1991) reinterpreted Burns mode.docxVinaOconner450
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.
Laura Jackson discusses three spatial scales on the aspects of phy.docxVinaOconner450
Laura Jackson discusses three spatial scales on the aspects of physical and mental health, and social and cultural vibrancy. What are the three spatial hierarchies of human settlements?
Robert Putnam presents 14 indicators of social capital into five categories. Describe each category, including the indicators that comprise it, and explain the role that each plays.
Spirn in the article
Urban Nature and Human Design
poses the following questions:
·
Does nature influence human development, or is man the sole architect of the environment in which he lives?
·
Should man seek to coexist with nature or to dominate nature?
·
Does man exist within nature or apart from it?
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In
Urban Nature and Human Design,
Lynch argues for a “good city” form. What does he mean by this, and what are the characteristics of a “good city”?
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Wachs argues that preferences for low-density living and a comprehensive highway program lead to urban sprawl. But he argues that regional rapid transit plans failed to gain acceptance. Why do you think this is the case?
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and
values
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Community Development covers range of goals and activities. Name each one and explain in details.
What are the origins of the urban renewal? What were some of the challenges and realities?
What are the differences between community development vs. urban renewal approach?
What role does housing play in relation to community development?
What are Collateralized Debt Obligations (CDOs)? What are the implications for the municipalities?
What factors have played a role in the federal, state, and local governments’ involvement in local economic development efforts?
What strategies do communities/community economic development agencies rely on to promote their economic growth? What are some of the pitfalls of these reliances?
What are the systematic approaches to economic development planning?
What are some of the reasons for growth management? Describe and explain each.
What are some of the challenges with local growth management programs?
What are different ways that one can define “smart-growth?”
What are some of the issues and concerns that proponents of smart growth advocate for?
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Using course theories and current multinational organizations that have locations in several countries, convey your own thoughts on the subject and address the following:
What leadership considerations must an organization weigh in selecting another country to open a location such as a manufacturing plant?
How might leaders need to change leadership styles to manage multinational locations?
What public relations issues might arise from such a decision?
How would you recommend such a company to demonstrate their social responsibility to their headquarters country as well as any offshore locations?
Please submit your assignment.
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Laws Enforcement TechnologiesIn this week’s assignment, you will e.docxVinaOconner450
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Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
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Social Laboratory, New Zealand,
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This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
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This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
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Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
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Andreas Schleicher presents PISA 2022 Volume III - Creative Thinking - 18 Jun...EduSkills OECD
Andreas Schleicher, Director of Education and Skills at the OECD presents at the launch of PISA 2022 Volume III - Creative Minds, Creative Schools on 18 June 2024.
CLA 2 PresentationBUS 606 Advanced Statistical Concepts An
1. CLA 2 Presentation
BUS 606 Advanced Statistical Concepts And Business Analytics
Agenda
Introduction
Multiple linear regression is the most appropriate statistical
technique in predicting the outcome of a dependent variable at
different values (Keith, 2019).
The study assessed the relationship between the cost of
constructing an LWR Plant and the three predictor variables S,
N, and CT.
We assessed the association between the two-test used to
examine the employee performance.
2. Assumption of Regression Analysis
Multicollinearity
Multicollinearity is the condition where the predictor variables
are highly correlated (Alin, 2010).
Correlation Analysis
4
Assumption of Regression Analysis Cont’
Normality test
The normality assumption is not violated after transforming the
outcome variable C, using natural log (C) (Shapiro-Wilk =
0.967, p = 0.414).
5
Results and Discussion – Regression Analysis
Use Residual Analysis and R2 to Check Your Model
3. The R-Squared of 0.232 indicates that the model can explain
about 23.2% of ln(C)
The low R-Square indicated that the model does not fit the data
well (Brown, 2009).
6
Results and Discussion Cont’
State which Variables are Important in predicting the cost of
constructing an LWR plant?
S is a significant contributing factor in predicting ln(C)(p =
0.021), but N and CT have no significant effect in predicting (p
> 0.05)
7
Results and Discussion Cont’
State a prediction equation that can be used to predict ln(C).
After dropping N and CT from the model since they do not have
a significance effect in predicting ln(C), the prediction equation
is given by:
4. Does adding CT improve R2? If so, by what amount?
Adding CT in the model changes R-Square by 0.001 from 0.232
to 0.234 which is not significant different from zero (p > 0.05).
8
Results and Discussion Cont’ - Correlational Analysis
Evaluate the correlation between the two scores and state if
there seems to be any association between the two.
There was a weak positive correlation between the two tests (r =
0.187). This suggested that the two test scores were not
correlated.
9
Results and Discussion Cont’
Find the probability of upgrading for each division of the
sample by the Bayes’ theorem.
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
5. = 23/43
10
Results and Discussion Cont’
Find the probability of upgrading for each division of the
sample by the naïve version of the Bayes’ theorem
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
= 23/43
11
Results and Discussion Cont’
Compare your results in parts b and c and explain the difference
or indifference based on observed probabilities
Naïve version and Bayes theorem have similar probabilities.
We have only one predictor in each sample division
This is because Naïve is applied with Bayes's theorem with an
assumption of independence between the features of predictor
variables (Webb, 2010).
12
6. Conclusion and Recommendations
– LWR Plant
Most of the variations of the outcome variable are explained by
variables not included in the model.
Further analysis indicated that the S predictor had a significant
effect in predicting the cost of constructing an LWR plant (C).
N and CT did not have a significant effect in predicting.
Should drop N and CT predictors from the model.
13
Conclusion and Recommendations
– Employee Performance
The analysis also indicated that the two test were not related
with each other but, the first test had the best ability in
discriminating than the second test.
Which suggested that the first test was the best to use in
predicting whether employees will be unsuccessful or successful
in the position.
14
References
Alin, A. (2010). Multicollinearity. Wiley Interdisciplinary
Reviews: Computational Statistics, 2(3), 370-374.
Brown, J. D. (2009). The coefficient of determination.
Daoud, J. I. (2017, December). Multicollinearity and regression
analysis. In Journal of Physics: Conference Series (Vol. 949,
No. 1, p. 012009). IOP Publishing.
Keith, T. Z. (2019). Multiple regression and beyond: An
7. introduction to multiple regression and structural equation
modeling. Routledge.
Puth, M. T., Neuhäuser, M., & Ruxton, G. D. (2014). Effective
use of Pearson's product–moment correlation
coefficient. Animal behaviour, 93, 183-189.
Webb, G. I. (2010). Naïve Bayes. Encyclopedia of machine
learning, 15, 713-714.
Kolmogorov-Smirnov
a
Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
ln_C .104 32 .200
*
.967 32 .414
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
Model R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .482
a
8. .232 .179 .34240 .232 4.385 2 29 .022
2 .483
b
.234 .151 .34814 .001 .052 1 28 .822
a. Predictors: (Constant), N, S
b. Predictors: (Constant), N, S, CT
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B Std. Error Beta Tolerance VIF
(Constant) 5.300 .277
19.161 .000
S .001 .000 .406 2.447 .021 .963 1.039
N .012 .010 .193 1.164 .254 .963 1.039
(Constant) 5.294 .283
18.718 .000
S .001 .000 .403 2.385 .024 .958 1.044
N .011 .010 .189 1.110 .276 .950 1.053
CT .028 .125 .038 .227 .822 .978 1.022
a. Dependent Variable: ln_C
2
9. Mohammed Alsaadi
Maria Claver
Gern 400
6/11/2021
Life Review: Proposal/Script
In life, every individual goes through unique
experiences during the different stages of their lives. It is
through these experiences that one is able to develop their
personal perspectives, judgments, and also acquire personal
strengths and wisdom. Much of what an individual is a today is
determined by the physical, emotional and mental experiences,
challenges and hardships that they have gone through in life.
For this proposal, I plan to interview my elderly
neighbour Salim, whom I have always been in awe of and who
has always fascinated me with his dinner conversation during
his visits. He is 67 years old and we have been neighbour for
more than 20 years. He and his family are very nice I spent
many times with them until they become like a family. The level
of this interview would be very comfortable and easy-going
since we know each other for a quite a long time. Furthermore,
this is a great chance to talk to him and learn more about his
10. experience growing up. I hope to learn from him about his
family background, his childhood, career and retirement and all
the significant experiences and events that have taken place in
his life. Through this interview, I expect to find out how one’s
life experiences can determine a person’s mental outlook and
physical conditions in the course of getting old. Apart from
acquiring information in this interview, I also intend to apply
the lessons and knowledge that I have accumulated in life also.
The questions in this interview will be containing components
of the biopsychosocial model, which entail biological,
psychological and social aspects that make up the reality of life
(Derek Bolton). To conclude, am hopeful of gaining a better
understanding of how these three aspects have influenced his
life and how it has affected both his mental and physical
health.
Biological Questions
1. When were you born? Do you know the date?
2. Can you describe the family background?
3. What was your childhood like and how were you brought up?
4. Who were your friends growing up, how did they influence
you? Are they still present in your life?
5. What are your opinions on the physical aspects of your life
and the changes to your body?
6. Do you suffer from health complication and if so, do you
need assistance in relation to the health complication?
7. What is your current diet and is it in relation to your health?
Psychological Questions
1. How do you perceive yourself and how would you describe
your life experiences?
2. What are some of the challenges that you have experienced in
your life and how have they influenced you? How were you able
to conquer these scenarios and how did it affect your life and
the person that you are today?
11. 3. What was your coping mechanism in overcoming the stress,
anxiety and frustration caused by the challenges in your life?
4. Would you change the past given an opportunity to go back
in time, and what would you do differently?
5. What do you think is most different today from when you
were growing up?
6. How has technology and telecommunication affected you? Do
you find it easy or hard to cope with this era of technology?
Social Questions
1. What is your support system, is it family or social support?
How has it changed your experience?
2. Do you have a written will or testament and what does it
entail? What are your views on nursing homes or specialized
facilities?
3. Are you happy with the life you have led and do you feel
happier, sad or depressed as you advanced in age?
4. What do you do in your spare time for fun? What do you find
most entertaining?
5. What is your legacy? What do you think you will be
remembered for?
6. What positive or negative impacts will you leave on the
world? Will you leave the world a better place than you found
it?
7.
Works Cited
Derek Bolton, Grant Gillett. The Biopsychosocial Model of
Health and Disease: New Philosophical and Scientific
Development. Springer, 2019.
THE BIOLOGY OF AGING 3
12. The Biology of Aging.
Alazhar Alsaadi
CSULB
Dr. Maria Claver
6/11/2021
Study of aging.
Abstract.
I got the opportunity to interview Mrs. Fatima Al-Saadi with
who we live in the same house. She suffers from back pains. I
got the chance to assess her life, the challenges that are facing
her, and how she was dealing with them. Further, we assessed
the cause and how the condition was being managed.
13. Proposal.
Mrs. Fatima, 75 years old, is my grandmother and we stay in the
same house. It is entrusted upon me the duty of caring for her.
She is of medium built and has a condition with her backbone
and as a result, it does not support her body well. As a result,
all her movement is through the use of a wheelchair.
Before conducting the interview, she must be prepared to give
her ample time to recollect herself and be prepared for the
questions. After preparation, the interview will take place after
a period of two days. One will take place on the first day of the
week after which she will be allowed to rest and the other will
take place on the third day of the week. The interview will take
place in the living room which is where she receives and
entertains guests and will be conducted in the mid-morning. The
timing will ensure that she is not too exhausted to give accurate
answers.
The reason I chose her as the subject of the interview was due
to the stories that she narrated about herself as a child. She was
a strong and hardworking lady before an illness at the age of 45
that affected her spinal cord and since then, she has never been
able to walk again. As a result, it arouses a curiosity within me
as I tried to figure out the cause of her medical condition, and
the resultant effect of this on her health and her perception of
life. Every time looking at her vibrant in her wheelchair, it
becomes more of a challenge to see her without it.
As a result of the curiosity to know what happened to my
grandmother, this assignment level is very comfortable. Further,
she accepted her condition and moved on and is also an
inspiration to us thus I was comfortable choosing her as a
recipient of this assignment. Besides, as a result of the bond
between us, we are free with each other thus making the
interview easier to conduct.
By the time I complete this assignment, I hope to have known
the cause of her illness, whether it can be cured, and whether it
14. is hereditary and if so, how to protect future generations. The
interview theory that I shall use is the biology of aging theory
because it deals with the human body and the damages as a
result of how it has been programmed.
Script.
Interview questions.
1. Can you elaborate on your life prior to the illness?
2. Are there activities that you used to regularly carry out
before the illness?
3. Was there anything that happened that could have triggered
the illness?
4. What were the initial signs and symptoms pf the condition?
5. Were you bullied?
6. How do you explain the illness to your friends and relatives?
7. Does questioning you about the diseases by any way make
you uncomfortable?
8. Do you feel as if you differ from other people?
9. What is the most challenging thing about being disabled?
10. What is your perception of self?
11. Do people treat you differently when they visit than they
once did?
12. Do you ever wish you were able to walk again?
13. Are the medication expenses a burden to you?
14. What does it feel like to be on medication on a daily basis?
15. How are you able to be so optimistic about life in your
condition?
16. Was the illness by any chance preventable? If it was, how
would you advise future generations to protect themselves?
Running Head: LOGISTIC REGRESSION AND
DISCRIMINANT ANALYSIS 1
LOGISTIC REGRESSION AND DISCRIMINANT ANALYSIS
9
15. LOGISTIC REGRESSION AND DISCRIMINANT ANALYSIS
NAME:
INSTRUCTOR:
DATE:
Part I
Logistic Regression
The age and gender of guests in a nursing home were examined
whether they are the cause of deaths in 2015. Data was
collected for gender, age and whether the guest died or not. In
this case, death is our dependent variable while age and gender
are the independent variables.
Since the dependent variable “died” was categorical with two
levels, this was an indication that logistic regression analysis
was suitable for prediction in this study (Austin & Merlo,
2017). The assumption of a dichotomous dependent variable
was met in this case where “died” took to values 0) No, 1) Yes.
The assumption of one or more predictor variables was met.
Age was quantitative reporting respective ages of the guests.
Gender was categorical with two levels 0) Females and 1)
Males.
Analysis
The collected data was analyzed to examine the
relationship between the predictor variables and the binary
16. dependent variable. A sample of 284 guests was used for this
study for easy analysis and generalizations. The overall logistic
regression model is given as;
Table 1 shows the total number of participants and the valid
sample that was utilized in this study.
Table 1: Logistic regression summary
The analysis showed that there were 144 successes and 140
failures. According to the results, the overall model was
statistically significant with χ2 (2) = 82.46, p < 0.001 (Warner,
2020). This implies that we can carry on with the analysis.
Analysis showed that gender and age were both statistically
significant and contributed to the variation in deaths. Gender
was statistically significant where b = 1.96, OR = 7.08, p < 0.05
implying it had an impact on deaths. Age was also statistically
significant where b = 0.196, OR = 1.22, p < 0.05. The
likelihood of dying is 7.08 times higher in males as compared to
females according to the odds ratio. Older people are 1.22 more
likely to succeed in the tests (Norton et al., 2018).
The logistic regression equation that helps in prediction of
death of a person given the age and gender will be given as;
Part II
Discriminant Analysis
Two tests were developed in a firm to determine whether some
of the employees will perform in a given position. A sample of
43 employees was examined. The main aim is to group
employees as either successful or unsuccessful by using the
tests given.
Discriminant analysis suits this case since exclusive grouping
was required and the dependent variable was categorical with
two groups 0) Unsuccessful and 1) Successful (Bowerman et al.,
2019). Two independent variables used in this study (Test 1 and
17. Test 2) were quantitative reporting the scores of the employees
in the two tests.
Analysis
Discriminant analysis was carried out in SPSS to classify the
employees as successful or unsuccessful based on the two tests.
Descriptive statistics were as shown in table 2.
Table 2: Descriptive statistics
Group Statistics
Group
Mean
Std. Deviation
Valid N (listwise)
Unweighted
Weighted
Unsuccessful
Test1
84.7500
4.24109
20
20.000
Test2
79.1000
4.38778
20
20.000
Successful
Test1
92.4348
3.47492
23
23.000
18. Test2
84.7826
6.23740
23
23.000
Total
Test1
88.8605
5.43175
43
43.000
Test2
82.1395
6.10847
43
43.000
The mean of test 1 in the unsuccessful group was 84.75 while
for test 2 in the unsuccessful group was 79.10. The means for
test 1 and 2 in the successful group were 92.43 and 84.78
respectively.
Table 3 shows the importance of the independent variables in
the discriminant function used to group the employees.
Table 3: Test of equality of group means
Tests of Equality of Group Means
Wilks' Lambda
F
df1
df2
Sig.
Test1
.490
42.644
1
19. 41
.000
Test2
.780
11.593
1
41
.001
According to the analysis, both tests scores were statistically
significant in for the discriminant function.
Table 4 shows the correlation matrix of the predictor variables.
Table 4: Correlation matrix
Pooled Within-Groups Matrices
Test1
Test2
Correlation
Test1
1.000
.187
Test2
.187
1.000
According to the analysis, the correlation between the scores of
test 1 and test 2 was r = 0.19. This is a weak positive
relationship implying the independent variables are not
correlated.
The assumption of multivariate normality was examined and the
test results were as shown in the Box’s M statistics given in
table 10 (Ul Hassan et al., 2017).
Table 5: Homogeneity of covariance matrix
Test Results
Box's M
20. 5.014
F
Approx.
1.582
df1
3
df2
936960.353
Sig.
.191
Tests null hypothesis of equal population covariance matrices.
According to the analysis, it is clear that groups did not differ
in the covariance matrices implying that the assumption is not
violated and the analysis can continue.
According to table 6, one discriminant function was found given
the two-grouped dependent variable.
Table 6: Canonical discriminant function
Eigenvalues
Function
Eigenvalue
% of Variance
Cumulative %
Canonical Correlation
1
1.161a
100.0
100.0
.733
a. First 1 canonical discriminant functions were used in the
analysis.
The strong positive canonical correlation implies that there was
21. a strong association between the discriminant function and the
dependent variable (Uurtio et al., 2017).
Table 7 shows the coefficients of the independent variables.
Table 7: Standardized canonical discriminant function
coefficients
Standardized Canonical Discriminant Function Coefficients
Function
1
Test1
.885
Test2
.328
According to the analysis, Test 1 had the best ability in
discriminating as compared to Test 2. This implies that Test 1 is
very significant in predicting whether employees will be
successful or unsuccessful in the position.
Table 8 shows the unstandardized canonical coefficients of the
model.
Table 8: Unstandardized canonical coefficients
Canonical Discriminant Function Coefficients
Function
1
Test1
.230
Test2
.060
(Constant)
-25.380
Unstandardized coefficients
The discriminant equation becomes;
D = -25.38 + 0.23*Test 1 + 0.06*Test 2
Table 9 shows the classification of the given variables.
22. Table 9: Classification
Classification Resultsa,c
Group
Predicted Group Membership
Total
Unsuccessful
Successful
Original
Count
Unsuccessful
16
4
20
Successful
5
18
23
%
Unsuccessful
80.0
20.0
100.0
Successful
21.7
78.3
23. 100.0
Cross-validatedb
Count
Unsuccessful
16
4
20
Successful
5
18
23
%
Unsuccessful
80.0
20.0
100.0
Successful
21.7
78.3
100.0
a. 79.1% of original grouped cases correctly classified.
b. Cross validation is done only for those cases in the analysis.
In cross validation, each case is classified by the functions
derived from all cases other than that case.
c. 79.1% of cross-validated grouped cases correctly classified.
Analysis showed that 80% of the employees classified as
unsuccessful were unsuccessful while 20% who were successful
were classified as unsuccessful. 78.30% successful employees
were classified as successful while 21.7% successful were
classified as unsuccessful. In overall, 79.10% cases were
24. correctly classified.
Reference
Austin, P. C., & Merlo, J. (2017). Intermediate and advanced
topics in multilevel logistic regression analysis. Statistics in
medicine, 36(20), 3257-3277.
Warner, R. M. (2012). Applied statistics: From bivariate
through multivariate techniques. Sage Publications.
Norton, E. C., Dowd, B. E., & Maciejewski, M. L. (2018). Odds
ratios—current best practice and use. Jama, 320(1), 84-85.
Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R.
M. Moniger, K. B., & Schur, P. J. (2019). Business
statistics and analytics in practice (9th ed.). McGraw-Hill
Ul Hassan, E., Zainuddin, Z., & Nordin, S. (2017). A review of
financial distress prediction models: logistic regression and
multivariate discriminant analysis. Indian-Pacific Journal of
Accounting and Finance, 1(3), 13-23.
Uurtio, V., Monteiro, J. M., Kandola, J., Shawe-Taylor, J.,
Fernandez-Reyes, D., & Rousu, J. (2017). A tutorial on
canonical correlation methods. ACM Computing Surveys
(CSUR), 50(6), 1-33.
25. Introduction
In this paper, I will use the cardUpgrade dataset to run the K
nearest neighbor algorithm in JMP and predict the likeli hood of
a customer upgrading to platinum status or not. This dataset has
three attributes:
a) UpGrade – this column contains categorical data represented
in nominal form.
b) Purchases – is a numeric column that describes the monetary
value of purchases made by each customer.
c) PlatProfile – this is also a categorical data that was used at
the time the customers signed up to evaluate whether they fit
the profile for a platinum member or not.
K Nearest Neighbors (KNN)
The K Nearest Neighbors algorithm is a supervised non-
parametric lazy learning algorithm applicable to either
classification or regression tasks (Okfalisa et al., 2017). First, a
supervised machine learning algorithm relies on labeled training
input to produce a desired output given non-labelled data.
Secondly, non-parametric means that the algorithm makes no
assumptions and any model built on it relies entirely on the
training data it is fed without further assumptions on the
structure of the data. Thirdly, the algorithm is lazy learning
meaning that it does not make any generalization since the
training is minimal. In essence, as opposed to most machine
learning algorithms, the training data used in a KNN model is
also used to test the model. KNN classifies a single data point
by comparing it to the points it is closest and most similar to. It
26. assumes that similar items exist in close proximity
KNN is apt for different ML tasks including decision-making
(as in this task), recommender systems, and image recognition.
For this particular task, I will use JMP to apply KNN on a
customer’s dataset. The model will compare the initial customer
profile attribute and purchase history to their current upgrade
status to be able to predict whether other customers would be
willing to upgrade or not. Because this is a classification task,
the output should be a discrete value that shows whether a
customer will upgrade or not. There is no middle ground which
is why the values are binary, that is, 0 or 1. The model will
have two predictors and a label. The output from this model will
also be nominal which means it represents the upgrade status of
an individual. While the output will be in the form of numerical
values (0 or 1), these numbers are only representational and
have no mathematical meaning (Ghattas et al., 2017).
KNN Scheme on JMP
First I imported the excel data set into JMP. The application
treats the two categorical columns as numeric. This must be
specified back to nominal in JMP. While this process is rather
limited, it is a form of data cleaning when creating a machine
learning model. Other data cleaning tasks typically include
identification and removal of duplicate records/observations and
finding ways to handle missing values. The second step is to
conduct an exploratory data analysis (EDA). According to Jebb
et al., this stage helps to decide the algorithm and variables that
would be used (2017). EDA also involves data visualization
which gives a cursory insight about the observations. For
instance, below is a bubble plot of UpGrade status against
purchases. It shows that those who did not upgrade are more
concentrated on the lower end of purchases while those who did
upgrade made higher purchase volumes. It also shows some
outliers which should be handled. I have chosen to ignore these
outliers because there are only one for each class meaning that
they would have minimal impact on the model. Additionally, the
dataset contains only forty observations, thus, there is very
27. little room for cropping out other observations.
I also visualized the distribution of the purchase column to
determine the percentage. The graph shows that the distribution
is almost split evenly (55% for non-upgrades and 45% for
upgrades).
Splitting the Data
For most machine learning modeling tasks, the data should only
be split into training and testing sets. The train-test approach is
used to avoid evaluating the model based on training dataset as
this would result in a biased score. Kuhn & Johnson state that it
is pragmatic for the model to be evaluated on data that was not
used to either build or finetune it (2013, p. 67). Some
algorithms including KNN, on the other hand, produce the best
results when the data is split into three including a validation
set. This third set is often seen as another set of test data, but it
is used to tune the hyperparameters of the model. However,
Touvron et al., elaborate that this splitting of the data into two
or three sets only produces optimal results when the dataset has
a large amount of data such that each class that could
potentially be observed is included in each set (2020).
Since this dataset only has forty observations, it cannot be split
thrice without compromising on model performance. It is,
instead, split into training and test sets at the ratio of 4:1. This
gives 32 observations for training and 8 observations for
testing. The KNN algorithm also expects a k value which is
typically selected as the square root of the total number of
observations. When there are only two classes to be predicted,
the standard practice is to pick an odd number to avoid a tie
during majority voting. For this reason, I have picked a 7 as the
value of k.
Confusion Matrix Interpretation
28. The confusion or error matrix is used to enhance the
understanding of a classification task. Simply reporting on the
accuracy of the model does not fully capture the performance of
the algorithm (Okfalisa et al., 2017). The precision and recall
scores are calculated from the output of the confusion matrix. In
the matrix, the predicted values are described as either positive
or negative whereas the actual values are resented as true or
false. In the end, there are four possibilities:
a) True Positive – these are the values that have been correctly
predicted by the model as positive and they are true.
b) True Negative – these values are actually true but the model
predicts them as negative.
c) False Positive – values predicted as positive yet they are
actually false
d) False Negative – these values have been predicted as false
and they are also negative.
In this case these values would be interpreted as follows:
a) True Positive (TP) – customers who did upgrade to platinum
and who the model has correctly predicted to have upgraded.
b) True Negative (TN) – customers predicted to upgrade yet did
not upgrade.
c) False Positive (FP) – customers predicted to not upgrade yet
they did upgrade.
d) False Negative (FN) – customers correctly predicted to not
have upgraded their cards to platinum.
The matrix for this model is as in the image below:
This means that the model produces 2 TPs, 0 TN, 1 FP, and 5
FN. Thus, only one out of the eight possible predictions is
incorrect. This model, therefore, has an accuracy score of 87.5%
PART 2
Using the Bayes theorem formula as indicated below, we can
calculate the probability that a customer who makes purchases
above 32.450 will also be likely to upgrade to platinum (Rouder
& Morey, 2018).
29. Below are the notations for the probabilities:
P(A) – the probability that a customer upgrades to platinum
(45%)
P(B) – the probability that a customer makes purchases equal to
or more than 32.450 (52.5%)
P(A|B) – the probability that a customer upgrades given that he
makes purchases equal to or above 32.450 (79.32%)
P(B|A) – the probability that a customer makes purchases equal
to or above 32.450 given that he has upgraded.
Thus P(B|A) = .9254, that is, 92.54% which is a significant
improvement from 87.5%. Therefore, using the Bayes theorem
formula, the model’s accuracy has been improved.
References
Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R.
M., Moniger, K. B., & Schur, P. J. (2019). Business statistics
and analytics in practice (pp. 186–189). Mcgraw-Hill Education.
Ghattas, B., Michel, P., & Boyer, L. (2017). Clustering nominal
data using unsupervised binary decision trees: Comparisons
with the state of the art methods. Pattern Recognition, 67, 177–
185. https://doi.org/10.1016/j.patcog.2017.01.031
Jebb, A. T., Parrigon, S., & Woo, S. E. (2017). Exploratory data
analysis as a foundation of inductive research. Human Resource
Management Review, 27(2), 265–276.
https://doi.org/10.1016/j.hrmr.2016.08.003
Kuhn, M., & Johnson, K. (2013). Applied Predictive Modeling.
In Google Books (p. 67). Springer Science & Business Media.
https://books.google.com/books/about/Applied_Predictive_Mod
eling.html?id=xYRDAAAAQBAJ&source=kp_book_description
Okfalisa, Gazalba, I., Mustakim, & Reza, N. G. I. (2017).
Comparative analysis of k-nearest neighbor and modified k-
nearest neighbor algorithm for data classification. 2017 2nd
International Conferences on Information Technology,
30. Information Systems and Electrical Engineering (ICITISEE).
https://doi.org/10.1109/icitisee.2017.8285514
Rouder, J. N., & Morey, R. D. (2018). Teaching Bayes’
Theorem: Strength of Evidence as Predictive Accuracy. The
American Statistician, 73(2), 186–190.
https://doi.org/10.1080/00031305.2017.1341334
Touvron, H., Vedaldi, A., Douze, M., & Jégou, H. (2020).
Fixing the train-test resolution discrepancy. ArXiv:1906.06423
[Cs]. https://arxiv.org/abs/1906.06423
Running Head: MERGING AND ACQUISITION
1
MERGING AND ACQUISITION
2
MERGING AND ACQUISITION
NAME:
INSTRUCTOR:
DATE:
Merging and Acquisition
Introduction
31. Some of the factors determining merger and acquisition
activities in retailing were examined in this paper to aid in
decision making that have a positive impact on a firm.
Characteristics of firms that were targeted for acquisition and
the firms that were willing to make acquisition were looked
into. Growth rate of sales for target firms and bidders were
tested to enable management make decision wisely on
acquisition (Christofi et al., 2017).
Growth rate of sales for target firms
The growth rate of sales for firms targeted for acquisition was
tested using normal distribution tests. A sample of 25 firms was
collected for this study. The mean sales growth rate was 0.16
and the standard deviation was 0.12. These are required in order
to test for normally distributed data (D’Agostino, 2017). We
perform t-test since the only sample statistics were known
(Emmert-Streib & Dehmer, 2019).
The research question for this study will be: Is there statistical
significant difference between the population mean and sample
mean for sales growth rate of target firms? The hypothesis
testing process was as given below;
Hypotheses
The following are the null and alternative hypotheses.
H0: μ = .10. The mean growth rate of sales for target firms is
not different from 10%
Ha: μ >.10. The mean growth rate of sales foe target firms
exceeds 10%.
Test statistics
T-test was carried out to examine whether the sales growth rate
of 0.16 was indeed statistically significant different from the
0.10.
The t-test is given as;
t =
= = 2.50
Calculate the degrees of freedom by 1 from the sample size
(Sung & Han, 2018);
df = 25 – 1 = 24
32. Determine the critical value from the t table at α = 0.10, 0.05,
0.01 and 0.001.
For α = 0.10, tα = 1.318 which is less than the calculated value
of t = 2.50 implying we reject the null hypothesis at α = 0.10
and conclude Ha: μ >.10.
For α = 0.05, tα = 1.711 which is less than the calculated value
of t = 2.50 implying we reject the null hypothesis at α = 0.05
and conclude Ha: μ >.10.
For α = 0.01, tα = 2.492 which is less than the calculated value
of t = 2.50 implying we reject the null hypothesis at α = 0.01
and conclude Ha: μ >.10.
For α = 0.001, tα = 3.467 which is less than the calculated value
of t = 2.50 implying we fail to reject the null hypothesis at α =
0.001 and conclude Ha: μ =.10.
Decision
There was very strong evidence to reject the null
hypothesis at α = 0.01 and we conclude that the mean growth
rate of sales for target firms exceeds 10% (Bowerman et al.,
2019).
Growth rate of sales for bidders
The growth rate for firms that were willing to make
acquisition was examined in order to come up with decisions
regarding acquisition. A sample size of 25 firms was collected
for analysis necessary for decision making. The mean growth
rate of sales was 0.12 and the standard deviation was 0.09. We
perform t-test since the only sample statistics were known;
Hypotheses Tested
Hypotheses to be tested;
H0: μ = .10. The mean growth rate of sales for bidders is not
different from 10%
Ha: μ >.10. The mean growth rate of sales foe bidders exceeds
10%.
Test statistics
33. T-test was carried out to examine whether the sales growth
rate of 0.12 was indeed statistically significant different from
the 0.10.
The t-test formula is given as follows;
t =
= = 1.111
Calculate the degrees of freedom by 1 from the sample size;
= 25 – 1 = 24
Determine the critical value from the t table at α = 0.10, 0.05,
0.01 and 0.001.
For α = 0.10, tα = 1.318 which is greater than the calculated
value of t = 1.111 implying we fail to reject the null hypothesis
at α = 0.10 and conclude Ha: μ = .10 (Trafimow, & Earp, 2017).
For α = 0.05, tα = 1.711 which is greater than the calculated
value of t = 1.111 implying we fail to reject the null hypothesis
at α = 0.10 and conclude Ha: μ = .10.
For α = 0.01, tα = 2.492 which is greater than the calculated
value of t = 1.111 implying we fail to reject the null hypothesi s
at α = 0.10 and conclude Ha: μ = .10.
For α = 0.001, tα = 3.467 which is greater than the calculated
value of t = 1.111 implying we fail to reject the null hypothesis
at α = 0.10 and conclude Ha: μ = .10.
Decision
We failed to reject the null hypothesis at α = 0.10 and conclude
that there was extremely evidence that the mean growth rate of
sales for bidders did NOT exceed 10%.
Conclusion
Analysis shows that the growth of sales for firms targeted
for acquisition exceeded 10% but the firms that were will ing to
place bids for acquisition had sales growth rate not exceeding
10%. The bidding firms should be analyzed critically to ensure
they meet the requirements of acquiring the already existing
firms that have great growth rate curves.
Reference
Christofi, M., Leonidou, E., & Vrontis, D. (2017). Marketing
34. research on mergers and acquisitions: a systematic review and
future directions. International Marketing Review.
D’Agostino, R. B. (2017). Tests for the normal distribution.
In Goodness-of-fit techniques (pp. 367-420). Routledge.
Emmert-Streib, F., & Dehmer, M. (2019). Understanding
statistical hypothesis Testing: the logic of statistical
inference. Machine Learning and Knowledge Extraction, 1(3),
945-961.
Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R.
M. Moniger, K. B., & Schur, P. J. (2019). Business
statistics and analytics in practice (9th ed.). McGraw-Hill
ISBN 9781260187496
Sung, W. P., & Han, T. Y. (Eds.). (2018, July). Exploration and
Practice of a New Formula for Calculating the Degree of
Freedom. In MATEC Web of Conferences (Vol. 175, p. 03018).
EDP Sciences.
Trafimow, D., & Earp, B. D. (2017). Null hypothesis
significance testing and Type I error: The domain
problem. New Ideas in Psychology, 45, 19-27.
Introduction
The prediction is the process of determining the magnitude of
predictors on the response variable. Prediction helps determine
the value of the outcome variable in the future using predictors
or factors included during the study. Moreover, multiple linear
regression is a statistical test used in assessing the relationship
between the response variable and more than one predictor
variable (Keith, 2019). Also, Cacoullos (2014) argued that
discriminant which is used in testing the equality of group
centroids is associated with multivariate analysis of variance
since it uses Wilks’ lambda applied in GLM multivariate
In this regard, multiple linear regression and discriminant
analysis are the most appropriate statistical techniques in
predicting the outcome of a dependent variable at different
35. values of the predictor variables and assess the contribution of
the predictors on the outcome and association between the
independent variable respectively (Keith, 2019). Besides, the
researcher can assess the variation of the outcome explained by
the independent variables included in the model. The test is
used in predicting the values of the response variable using
more than one predictor variable. Discriminant analysis was
used to assess the association between the two tests that were
developed in a firm to examine employee performance. The
study used a sample of 43 employees who were grouped as
either successful or unsuccessful and performed the two test to
assess their performance in a given position. Before conducting
both multiple linear regression and discriminant, it is good to
check whether the variables meet the necessary assumptions.
For multiple linear regression dependent variable must be
continuous and approximately normally distributed, while the
predictor variables can either be continuous or categorical. For
discriminant analysis the dependent variable must be divided
into two or more groups. Besides, the predictor variables should
not be correlated with each other, or there should be no
multicollinearity (Alin, 2010) for both statistical tests. This can
be assessed using the variance inflation factor, which should be
less than ten, or through correlation coefficients between the
predictor variables. The current study assessed the relationship
between the cost of constructing an LWR plant and the three
predictor variables S, N, and CT and assessed the association
between the two test used to examine the employee
performance.
Assumption of Regression Analysis
Multicollinearity
Correlation analysis is used in determining the strength and
direction of association between two variables (Puth et al.,
2014). The Pearson correlation coefficient is used for testing
the strength and direction of association between two variables
with a continuous level of measurement. However, when the
variables have an ordinal level of measurement, we use the
36. Spearman rank correlation coefficient (Puth et al., 2014). The
Pearson correlation coefficient ranges from -1 to 1, with -1 or 1
indicating perfect correlation and zero indicating no cor relation.
Table 1: Correlation Analysis
S
N
S
Pearson Correlation
1
.193
Sig. (2-tailed)
.289
N
32
32
N
Pearson Correlation
.193
1
Sig. (2-tailed)
.289
N
32
32
The correlation analysis in table 1 above indicates that the
correlation between the two predictor variables (S and N) is
positively weak and not significant at 0.05 level of significance
37. (r = 0.289, p = 0.193). This suggested that multicollinearity
does not exist and the assumption multicollinearity is not
violated. Furthermore, based on the analysis, the variance
inflation factor (VIF) is less than 10 (Daoud, 2017, December),
suggesting that the multicollinearity assumption is not violated.
Normality test
Table 2: Tests of Normality
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
ln_C
.104
32
.200*
.967
32
.414
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
The test of normality of the dependent variable (ln(C)) revealed
that the normality assumption is not violated after transforming
the variable C, using natural log at 0.05 level of significance
(Shapiro-Wilk = 0.967, p = 0.414).
Results and discussion
Regression Analysis
a. Use residual analysis and R2 to check your model.
38. Table 3: Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Change Statistics
R Square Change
F Change
df1
df2
Sig. F Change
1
.482a
.232
.179
.34240
.232
4.385
2
29
.022
2
.483b
.234
.151
.34814
.001
.052
1
28
39. .822
a. Predictors: (Constant), N, S
b. Predictors: (Constant), N, S, CT
The R-Squared of 0.232 indicates that the model can explain
about 23.2% of ln(C) variation and 76.8% of the variation is
explained by other variables not included in the model. Besides,
the analysis indicated high residuals. The low R-Square and
high residuals indicated that the model does not fit the data well
(Brown, 2009).
b. State which variables are important in predicting the cost of
constructing an LWR plant?
c. Table 4: Regression Coefficients
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
Collinearity Statistics
B
Std. Error
Beta
Tolerance
VIF
1
(Constant)
5.300
.277
19.161
.000
41. N
.011
.010
.189
1.110
.276
.950
1.053
CT
.028
.125
.038
.227
.822
.978
1.022
a. Dependent Variable: ln_C
The regression analysis displayed in table 4 above indicates that
S is a significant contributing factor in predicting ln(C) at a
0.05 level of significance (p = 0.021). However, the predictor
variable N does not significantly predict the ln(C) at a 0.05
level of significance (p = 0.254). According to the analysis,
there is no significant difference in ln(C) between the two
levels of the cooling tower (p = 0.822), suggesting that the
dummy variable CT does not have a significant effect in
predicting ln(C). Therefore, the researcher used the S predictor
to predict the cost of constructing an LWR plant but removed N
and CT from the model.
c. State a prediction equation that can be used to predict ln(C).
After dropping N and CT from the model since they do not have
a significance effect in predicting ln(C), the prediction equation
is given by:
42. d. Does adding CT improve R2? If so, by what amount?
Based on the analysis displayed on table 3 above, there is no
significant improvement in R-Squared after adding CT (p =
0.822). Adding CT in the model changes R-Square by 0.001
from 0.232 to 0.234 which is not significant different from zero.
Correlational Analysis
a. Evaluate the correlation between the two scores and state if
there seems to be any association between the two.
Table 5: Pooled Within-Groups Matrices
Test1
Test2
Correlation
Test1
1.000
.187
Test2
.187
1.000
The correlation analysis is shown in table 5 above indicates that
there was a weak positive correlation between the two tests (r =
0.187). This suggested that the two test scores were not
correlated.
b. Find the probability of upgrading for each division of the
sample by the Bayes’ theorem.
Given that: P(T1) = 43/86; P(T2) = 43/86
P (T1/Up) = 23/46; P (T2/Up) = 23/46
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
= 23/43
c. Find the probability of upgrading for each division of the
43. sample by the naïve version of the Bayes’ theorem.
P(Up/T1) = P (T1/Up) P(Up) ÷ P(T1)
= (23/46*46/86) ÷43/86
= 23/43
P(Up/T2) = P (T2/Up) P(Up) ÷ P(T2)
= (23/46*46/86) ÷43/86
= 23/43
d. Compare your results in parts b and c and explain the
difference or indifference based on observed probabilities
Since we have only one predictor in each sample division, the
naïve version and Bayes theorem have similar probabilities.
There is indifference based on observed probabilities. This is
because it is applied with Bayes's theorem with an assumption
of independence between the features of predictor variables
(Webb, 2010).
Conclusion and Recommendations
The analysis revealed that the model with the three predictors
predicting the cost of constructing an LWR plant does not fit
the data well. This suggested that most of the variations of the
outcome variable are explained by variables not included in the
model. Further analysis indicated that the S predictor had a
significant effect in predicting the cost of constructing an LWR
plant (C). However, N and CT did not have a significant effect
in predicting. Therefore, the researcher should drop N and CT
predictors from the model and only use the S predictor in
predicting the cost of constructing the LWR plant. The analysis
also indicated that the two test were not associated with each
other but, the first test had the best potential in discriminating
than the second test. Which suggested that the first test was the
best to use in predicting whether employees will be
unsuccessful or successful in the position.
Nevertheless, the study did not control for alternative
explanations that would affect the validity of the findings.
Further study is needed that will include variables with a good
fit of the data to help in predicting the cost of constructing an
LWR plant. In addition, a study that will control all possible
44. confounding is required to help in the prediction of the outcome
variable and assessing the best test in predicting employee
performance.
References
Alin, A. (2010). Multicollinearity. Wiley Interdisciplinary
Reviews: Computational Statistics, 2(3), 370-374.
Brown, J. D. (2009). The coefficient of determination.
Cacoullos, T. (Ed.). (2014). Discriminant analysis and
applications. Academic Press.
Daoud, J. I. (2017, December). Multicollinearity and regression
analysis. In Journal of Physics: Conference Series (Vol. 949,
No. 1, p. 012009). IOP Publishing.
Keith, T. Z. (2019). Multiple regression and beyond: An
introduction to multiple regression and structural equation
modeling. Routledge.
Puth, M. T., Neuhäuser, M., & Ruxton, G. D. (2014). Effective
use of Pearson's product–moment correlation
coefficient. Animal behaviour, 93, 183-189.
Webb, G. I. (2010). Naïve Bayes. Encyclopedia of machine
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