For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all
Psyc 355 Effective Communication / snaptutorial.comHarrisGeorg39
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all but:
For more course tutorials visit
www.tutorialrank.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
Psyc 355 Effective Communication - tutorialrank.comBartholomew88
For more course tutorials visit
www.tutorialrank.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the
This document provides an overview of starting SPSS, including installing the software, opening SPSS, the main SPSS windows, entering and saving data, and conducting statistical analysis. It discusses the SPSS data editor interface, defining variables, entering data by copying from Excel or directly into SPSS, and saving SPSS files. It also briefly mentions bibliographic citations for SPSS.
This document provides an overview of statistical analysis of questionnaire data. It discusses topics like questionnaire construction, data entry, reliability analysis using Cronbach's alpha, descriptive statistics for Likert scale items including frequencies, medians, interquartile ranges and box plots. It also covers composite scale analysis using means, standard deviations and comparisons between groups. An example is provided on assessing student satisfaction regarding teaching using 4 questionnaire items from 60 students. Results would be reported using tables and figures with interpretations.
Psyc 355 Effective Communication / snaptutorial.comHarrisGeorg39
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all but:
For more course tutorials visit
www.tutorialrank.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
Psyc 355 Effective Communication - tutorialrank.comBartholomew88
For more course tutorials visit
www.tutorialrank.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the
This document provides an overview of starting SPSS, including installing the software, opening SPSS, the main SPSS windows, entering and saving data, and conducting statistical analysis. It discusses the SPSS data editor interface, defining variables, entering data by copying from Excel or directly into SPSS, and saving SPSS files. It also briefly mentions bibliographic citations for SPSS.
This document provides an overview of statistical analysis of questionnaire data. It discusses topics like questionnaire construction, data entry, reliability analysis using Cronbach's alpha, descriptive statistics for Likert scale items including frequencies, medians, interquartile ranges and box plots. It also covers composite scale analysis using means, standard deviations and comparisons between groups. An example is provided on assessing student satisfaction regarding teaching using 4 questionnaire items from 60 students. Results would be reported using tables and figures with interpretations.
The document discusses key considerations for designing questionnaires, including:
1. The format of questions will affect the answers, so questions should be short (under 25 words), understandable, and avoid double negatives.
2. Choosing an appropriate question format is important so responses are understandable and analyzable. Questions types include single answers, multiple choices, scales, and grids.
3. Pilot testing the questionnaire is essential to check that the data can be analyzed as intended and to refine ambiguous, leading, or poorly structured questions. Feedback from pilot participants should be solicited.
4. Generally, questionnaires should be limited to around 20 likert-scale questions to maintain participant interest and engagement. A variety of
This document provides an overview of reliability analysis and factor analysis. It discusses the concepts of validity, reliability, and their importance in scientific research. Reliability is defined as the consistency or dependability of measurement, and is assessed using reliability analysis techniques like Cronbach's alpha. Factor analysis is introduced as a technique to simplify complex constructs into underlying dimensions or factors. The key steps of factor analysis include examining the correlation matrix, extracting initial factors using methods like principal component analysis, and rotating factors to arrive at the final factor solution. Decisions on the number of factors are based on statistical criteria like eigenvalues and scree plots, as well as conceptual grounds.
Exploratory factor analysis (EFA) is a statistical technique used to identify the underlying relationships between measured variables. EFA can group variables into a smaller number of factors and reduce complexity in the data. The document discusses EFA methodology, including conducting EFA in SPSS, determining the number of factors, rotating factors, and interpreting results. Assumptions of EFA and different extraction and rotation methods are also covered.
The use of data and its modelling in science provides meaningful interpretation of real world problems. This presentation provides an easy to understand overview of data visualization and analytics , and snippets of data science applications using R - programming.
Non-parametric tests are used when data is not normally distributed. They analyze rankings of raw scores rather than means. The Mann-Whitney and Wilcoxon rank-sum tests compare two independent groups and are equivalent to a t-test. They ignore groupings and rank all data points, expecting similar ranks between groups if they are the same. The Kruskal-Wallis test compares multiple groups and is akin to an ANOVA. Chi square examines relationships between categorical variables by comparing observed and expected frequencies in a contingency table to determine if differences are due to chance.
This document discusses non-parametric tests, which are statistical tests that make fewer assumptions about the population distribution compared to parametric tests. Some key points:
1) Non-parametric tests like the chi-square test, sign test, Wilcoxon signed-rank test, Mann-Whitney U-test, and Kruskal-Wallis test are used when the population is not normally distributed or sample sizes are small.
2) They are applied in situations where data is on an ordinal scale rather than a continuous scale, the population is not well defined, or the distribution is unknown.
3) Advantages are that they are easier to compute and make fewer assumptions than parametric tests,
This document provides an overview of non-parametric statistical tests. It discusses tests such as the chi-square test, Wilcoxon signed-rank test, Mann-Whitney test, Friedman test, and median test. These tests can be used with ordinal or nominal data when the assumptions of parametric tests are not met. The document explains the appropriate uses and procedures for each non-parametric test.
The document discusses parametric and non-parametric tests. It provides examples of commonly used non-parametric tests including the Mann-Whitney U test, Kruskal-Wallis test, and Wilcoxon signed-rank test. For each test, it gives the steps to perform the test and interpret the results. Non-parametric tests make fewer assumptions than parametric tests and can be used when the data is ordinal or does not meet the assumptions of parametric tests. They provide a distribution-free alternative for analyzing data.
The document discusses factor analysis as an exploratory and confirmatory multivariate technique. It explains that factor analysis is commonly used for data reduction, scale development, and evaluating the dimensionality of variables. Factor analysis determines underlying factors or dimensions from a set of interrelated variables. It reduces a large number of variables to a smaller number of factors. The key steps in factor analysis include computing a correlation matrix, extracting factors, rotating factors, and making decisions on the number of factors.
This presentation deals with the basics of design of experiments and discusses all the three basic statistical designs i.e. CRD, RBD and LSD. Further it explains the guidelines for developing experimental research.
The presentation covered key steps in analyzing survey data including defining goals, designing valid and reliable survey questions, collecting data, cleaning data, conducting descriptive statistics and correlations, comparing mean differences between groups, and clearly presenting results along with conclusions and recommendations. Piloting surveys and continuously improving methods was also emphasized.
This document discusses non-parametric statistical tests, which make few assumptions about the distribution of the underlying population. It provides examples of non-parametric tests like the sign test, Wilcoxon rank sum test, and Kruskal-Wallis test. These tests involve ranking all observations from different groups together and applying statistical tests to the ranks rather than the original values. Non-parametric tests are useful when assumptions of parametric tests may not hold but lack power with small samples.
Amrita Kumari from Banaras Hindu University submitted an application discussing parametric tests. Parametric tests were developed by R. Fisher and make assumptions about the population distribution from which a sample is drawn. The key assumptions are that the population is normally distributed, observations are independent, populations have equal variance, and data is on a ratio or interval scale. Parametric tests can be used even when distributions are skewed or variances differ, and they have more statistical power than non-parametric tests. Common parametric tests include t-tests, z-tests, and ANOVA. The document then discusses one-sample, dependent, and independent t-tests in more detail. Both advantages like precision and disadvantages like sensitivity
The document discusses several non-parametric tests that can be used as alternatives to parametric tests when the assumptions of parametric tests are violated. Specifically, it discusses:
1. The sign test and one sample median test, which can be used instead of t-tests when the data is skewed or not normally distributed.
2. Mood's median test, which compares the medians of two independent samples and is the nonparametric version of a one-way ANOVA.
3. The Kruskal-Wallis test, which determines if there are differences in medians across three or more groups and is the nonparametric version of a one-way ANOVA.
This document provides an overview of statistical tools used in research. It begins with an introduction to statistics and discusses descriptive and inferential statistics. Descriptive statistics summarize data through measures like the mean, median and mode, while inferential statistics make inferences about a population based on a sample. Both parametric and non-parametric statistical tests are covered. Common parametric tests include the t-test and ANOVA, which assume a normal distribution, while non-parametric tests like the chi-squared test are used when distributions are unknown. The document also reviews variables, types of data, statistical software options and includes examples and quizzes.
This document provides an introduction and overview of non-parametric statistical methods, including ranks and the median, Wilcoxon signed rank test, Mann-Whitney test, and Spearman's rank correlation coefficient. It defines what non-parametric tests are, discusses their advantages over parametric tests in situations where data is not normally distributed, and provides examples of calculating and interpreting several non-parametric tests in SPSS.
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all but:
9. We have learned three t tests, including all of the following except
Assignment 2 Tests of SignificanceThroughout this assignment yo.docxrock73
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies. You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables. You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how every question should be formatted. You will complete all of the problems. Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses. All calculations should be coming from your SPSS. You will need to submit the SPSS output file to get credit for this assignment. This file will save as a .spv file and will need to be in a single file. In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
1. State your research hypothesis (H1) and null hypothesis (H0).
2. Identify your confidence interval (.05 or .01)
3. Conduct your analysis using SPSS.
4. Look for the valid score for comparison. This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’. We will call this “p”.
5. Compare the two and apply the following rule:
a. If “p” is < or = confidence interval, than you reject the null.
Be sure to explain to the reader what this means in regards to your study. (Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable. Perhaps you bold your font or use a different color.
ASSIGNMENT 2(200) WORD MINIUM
1. They allow us to see if our relationship is "statistically significant". (Remember that this only shows us that there is or is not a relationship but does NOT show us if it is big, small, or in-between.)
2. It let's us know if our findings can be generalized to the population which our sample was selected from and represents.
This week you will decide which test of significance you will use for your project. For this class your choices for tests will include one of the following:
· Chi-square
· t Test
· ANOVA
We will be using a process for hypothesis testing which outlines five steps researchers can follow to complete this process:
1. Write your research hypothesis (H1) and your null hypothesis (H0).
2. Identify and record your confidence interval. These are usually .05 (95%) or .01 (99%).
3. Complete the test using SPSS.
4. Identify the number under Sig. (2-tail). This will be represented by "p".
5. Compare the numbers in steps 2 and 4 and apply the following rule:
1. If p < or = confidence interval, than you reject the null hypothesis
Determine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain how that impacts your research and best describes the relationship between variables.
TEST QUESTIONS-NEED FULL ANSWERS
Q1
Make up and discuss research examples corresponding to the various ...
PSYC 354Homework 8Single-Sample T-TestWhen submitting this f.docxpotmanandrea
This homework assignment involves analyzing data using SPSS and answering conceptual questions about hypothesis testing, z-tests, percentiles, and effect sizes. It covers four parts: concepts, SPSS analysis using provided data sets, additional questions requiring calculations, and a cumulative section involving descriptive statistics and graphs in SPSS. Students are instructed to complete analyses in SPSS and paste outputs and graphs into their homework document along with answering written questions.
The document discusses key considerations for designing questionnaires, including:
1. The format of questions will affect the answers, so questions should be short (under 25 words), understandable, and avoid double negatives.
2. Choosing an appropriate question format is important so responses are understandable and analyzable. Questions types include single answers, multiple choices, scales, and grids.
3. Pilot testing the questionnaire is essential to check that the data can be analyzed as intended and to refine ambiguous, leading, or poorly structured questions. Feedback from pilot participants should be solicited.
4. Generally, questionnaires should be limited to around 20 likert-scale questions to maintain participant interest and engagement. A variety of
This document provides an overview of reliability analysis and factor analysis. It discusses the concepts of validity, reliability, and their importance in scientific research. Reliability is defined as the consistency or dependability of measurement, and is assessed using reliability analysis techniques like Cronbach's alpha. Factor analysis is introduced as a technique to simplify complex constructs into underlying dimensions or factors. The key steps of factor analysis include examining the correlation matrix, extracting initial factors using methods like principal component analysis, and rotating factors to arrive at the final factor solution. Decisions on the number of factors are based on statistical criteria like eigenvalues and scree plots, as well as conceptual grounds.
Exploratory factor analysis (EFA) is a statistical technique used to identify the underlying relationships between measured variables. EFA can group variables into a smaller number of factors and reduce complexity in the data. The document discusses EFA methodology, including conducting EFA in SPSS, determining the number of factors, rotating factors, and interpreting results. Assumptions of EFA and different extraction and rotation methods are also covered.
The use of data and its modelling in science provides meaningful interpretation of real world problems. This presentation provides an easy to understand overview of data visualization and analytics , and snippets of data science applications using R - programming.
Non-parametric tests are used when data is not normally distributed. They analyze rankings of raw scores rather than means. The Mann-Whitney and Wilcoxon rank-sum tests compare two independent groups and are equivalent to a t-test. They ignore groupings and rank all data points, expecting similar ranks between groups if they are the same. The Kruskal-Wallis test compares multiple groups and is akin to an ANOVA. Chi square examines relationships between categorical variables by comparing observed and expected frequencies in a contingency table to determine if differences are due to chance.
This document discusses non-parametric tests, which are statistical tests that make fewer assumptions about the population distribution compared to parametric tests. Some key points:
1) Non-parametric tests like the chi-square test, sign test, Wilcoxon signed-rank test, Mann-Whitney U-test, and Kruskal-Wallis test are used when the population is not normally distributed or sample sizes are small.
2) They are applied in situations where data is on an ordinal scale rather than a continuous scale, the population is not well defined, or the distribution is unknown.
3) Advantages are that they are easier to compute and make fewer assumptions than parametric tests,
This document provides an overview of non-parametric statistical tests. It discusses tests such as the chi-square test, Wilcoxon signed-rank test, Mann-Whitney test, Friedman test, and median test. These tests can be used with ordinal or nominal data when the assumptions of parametric tests are not met. The document explains the appropriate uses and procedures for each non-parametric test.
The document discusses parametric and non-parametric tests. It provides examples of commonly used non-parametric tests including the Mann-Whitney U test, Kruskal-Wallis test, and Wilcoxon signed-rank test. For each test, it gives the steps to perform the test and interpret the results. Non-parametric tests make fewer assumptions than parametric tests and can be used when the data is ordinal or does not meet the assumptions of parametric tests. They provide a distribution-free alternative for analyzing data.
The document discusses factor analysis as an exploratory and confirmatory multivariate technique. It explains that factor analysis is commonly used for data reduction, scale development, and evaluating the dimensionality of variables. Factor analysis determines underlying factors or dimensions from a set of interrelated variables. It reduces a large number of variables to a smaller number of factors. The key steps in factor analysis include computing a correlation matrix, extracting factors, rotating factors, and making decisions on the number of factors.
This presentation deals with the basics of design of experiments and discusses all the three basic statistical designs i.e. CRD, RBD and LSD. Further it explains the guidelines for developing experimental research.
The presentation covered key steps in analyzing survey data including defining goals, designing valid and reliable survey questions, collecting data, cleaning data, conducting descriptive statistics and correlations, comparing mean differences between groups, and clearly presenting results along with conclusions and recommendations. Piloting surveys and continuously improving methods was also emphasized.
This document discusses non-parametric statistical tests, which make few assumptions about the distribution of the underlying population. It provides examples of non-parametric tests like the sign test, Wilcoxon rank sum test, and Kruskal-Wallis test. These tests involve ranking all observations from different groups together and applying statistical tests to the ranks rather than the original values. Non-parametric tests are useful when assumptions of parametric tests may not hold but lack power with small samples.
Amrita Kumari from Banaras Hindu University submitted an application discussing parametric tests. Parametric tests were developed by R. Fisher and make assumptions about the population distribution from which a sample is drawn. The key assumptions are that the population is normally distributed, observations are independent, populations have equal variance, and data is on a ratio or interval scale. Parametric tests can be used even when distributions are skewed or variances differ, and they have more statistical power than non-parametric tests. Common parametric tests include t-tests, z-tests, and ANOVA. The document then discusses one-sample, dependent, and independent t-tests in more detail. Both advantages like precision and disadvantages like sensitivity
The document discusses several non-parametric tests that can be used as alternatives to parametric tests when the assumptions of parametric tests are violated. Specifically, it discusses:
1. The sign test and one sample median test, which can be used instead of t-tests when the data is skewed or not normally distributed.
2. Mood's median test, which compares the medians of two independent samples and is the nonparametric version of a one-way ANOVA.
3. The Kruskal-Wallis test, which determines if there are differences in medians across three or more groups and is the nonparametric version of a one-way ANOVA.
This document provides an overview of statistical tools used in research. It begins with an introduction to statistics and discusses descriptive and inferential statistics. Descriptive statistics summarize data through measures like the mean, median and mode, while inferential statistics make inferences about a population based on a sample. Both parametric and non-parametric statistical tests are covered. Common parametric tests include the t-test and ANOVA, which assume a normal distribution, while non-parametric tests like the chi-squared test are used when distributions are unknown. The document also reviews variables, types of data, statistical software options and includes examples and quizzes.
This document provides an introduction and overview of non-parametric statistical methods, including ranks and the median, Wilcoxon signed rank test, Mann-Whitney test, and Spearman's rank correlation coefficient. It defines what non-parametric tests are, discusses their advantages over parametric tests in situations where data is not normally distributed, and provides examples of calculating and interpreting several non-parametric tests in SPSS.
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all but:
9. We have learned three t tests, including all of the following except
Assignment 2 Tests of SignificanceThroughout this assignment yo.docxrock73
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies. You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables. You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how every question should be formatted. You will complete all of the problems. Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses. All calculations should be coming from your SPSS. You will need to submit the SPSS output file to get credit for this assignment. This file will save as a .spv file and will need to be in a single file. In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
1. State your research hypothesis (H1) and null hypothesis (H0).
2. Identify your confidence interval (.05 or .01)
3. Conduct your analysis using SPSS.
4. Look for the valid score for comparison. This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’. We will call this “p”.
5. Compare the two and apply the following rule:
a. If “p” is < or = confidence interval, than you reject the null.
Be sure to explain to the reader what this means in regards to your study. (Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable. Perhaps you bold your font or use a different color.
ASSIGNMENT 2(200) WORD MINIUM
1. They allow us to see if our relationship is "statistically significant". (Remember that this only shows us that there is or is not a relationship but does NOT show us if it is big, small, or in-between.)
2. It let's us know if our findings can be generalized to the population which our sample was selected from and represents.
This week you will decide which test of significance you will use for your project. For this class your choices for tests will include one of the following:
· Chi-square
· t Test
· ANOVA
We will be using a process for hypothesis testing which outlines five steps researchers can follow to complete this process:
1. Write your research hypothesis (H1) and your null hypothesis (H0).
2. Identify and record your confidence interval. These are usually .05 (95%) or .01 (99%).
3. Complete the test using SPSS.
4. Identify the number under Sig. (2-tail). This will be represented by "p".
5. Compare the numbers in steps 2 and 4 and apply the following rule:
1. If p < or = confidence interval, than you reject the null hypothesis
Determine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain how that impacts your research and best describes the relationship between variables.
TEST QUESTIONS-NEED FULL ANSWERS
Q1
Make up and discuss research examples corresponding to the various ...
PSYC 354Homework 8Single-Sample T-TestWhen submitting this f.docxpotmanandrea
This homework assignment involves analyzing data using SPSS and answering conceptual questions about hypothesis testing, z-tests, percentiles, and effect sizes. It covers four parts: concepts, SPSS analysis using provided data sets, additional questions requiring calculations, and a cumulative section involving descriptive statistics and graphs in SPSS. Students are instructed to complete analyses in SPSS and paste outputs and graphs into their homework document along with answering written questions.
WEEK 6 – EXERCISES Enter your answers in the spaces pr.docxwendolynhalbert
WEEK 6 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week6_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
1
.
A psychotherapist studied whether his clients self-disclosed more while sitting in an easy chair or lying down on a couch. All clients had previously agreed to allow the sessions to be videotaped for research purposes. The therapist randomly assigned 10 clients to each condition. The third session for each client was videotaped and an independent observer counted the clients’ disclosures. The therapist reported that “clients made more disclosures when sitting in easy chairs (
M
= 18.20) than when lying down on a couch (
M
= 14.31),
t
(18) = 2.84,
p
< .05, two-tailed.” Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
2.
A researcher compared the adjustment of adolescents who had been raised in homes that were either very structured or unstructured. Thirty adolescents from each type of family completed an adjustment inventory. The results are reported in the table below. Explain these results to a person who understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Means on Four Adjustment Scales for
Adolescents from Structured versus Unstructured Homes
Scale
Structured Homes
Unstructured Homes
t
Social Maturity
106.82
113.94
–1.07
School Adjustment
116.31
107.22
2.03*
Identity Development
89.48
94.32
1.93*
Intimacy Development
102.25
104.33
.32
______________________
*
p
< .05
3.
Do men with higher levels of a particular hormone show higher levels of assertiveness? Levels of this hormone were tested in 100 men. The top 10 and the bottom 10 were selected for the study. All participants took part in a laboratory simulation in which they were asked to role-play a person picking his car up from a mechanic’s shop. The simulation was videotaped and later judged by independent raters on each of four types of assertive statements made by the participant. The results are shown in the table below. Explain these results to a person who fully understands the
t
test for a single sample but knows nothing about the
t
test for independent means.
Mean Number of Assertive Statements
Type of Assertive Statement
Group
1
2
3
4
Men with High Levels
2.14
1.16
3.83
0.14
Men with Low Levels
1.21
1.32
2.33
0.38
t
3.81**
0.89
2.03*
0.58
______________________
*
p
< .05;
**
p
< 0.1
4.
A manager of a small store wanted to discourage shoplifters by putting signs around the store saying “Shoplifting is a crime!” However, he wanted to make sure this would not result in customers buying less. To test this, he displayed the signs every other W.
The slides discuss comparing two means to ascertain which mean is of greater statistical significance. In these slides we will learn about three research questions in which the t-test can be used to analyze the data and compare the means from two independent groups, two paired samples, and a sample and a population.
tutor2u Strong Foundations A Level Psychologytutor2u
Browse the student workshop booklet for our A Level Psychology Strong Foundations exam-skills and revision workshop. For more information on how to attend the A Level Psychology Strong Foundations workshops, please visit http://www.tutor2u.net/events/a-level-psychology-strong-foundations-workshops
WEEK 5 – EXERCISES Enter your answers in the spaces pr.docxpaynetawnya
WEEK 5 – EXERCISES
Enter your answers in the spaces provided. Save the file using your last name as the beginning of the file name (e.g., ruf_week5_exercises) and submit via “Assignments.” When appropriate,
show your work
. You can do the work by hand, scan/take a digital picture, and attach that file with your work.
For the following question(s): A school counselor tests the level of depression in fourth graders in a particular class of 20 students. The counselor wants to know whether the kind of students in this class differs from that of fourth graders in general at her school. On the test, a score of 10 indicates severe depression, while a score of 0 indicates no depression. From reports, she is able to find out about past testing. Fourth graders at her school usually score 5 on the scale, but the variation is not known. Her sample of 20 fifth graders has a mean depression score of 4.4. Use the .01 level of significance.
1.
The counselor calculates the unbiased estimate of the population’s variance to be 15. What is the variance of the distribution of means?
A)
15/20 = 0.75
B)
15/19 = 0.79
C)
15
2
/20 = 11.25
D)
15
2
/19 = 11.84
2.
Suppose the counselor tested the null hypothesis that fourth graders in this class were
less
depressed than those at the school generally. She figures her
t
score to be
-
.20. What decision should she make regarding the null hypothesis?
A)
Reject it
B)
Fail to reject it
C)
Postpone any decisions until a more conclusive study could be conducted
D)
There is not enough information given to make a decision
3.
Suppose the standard deviation she figures (the square root of the unbiased estimate of the population variance) is .85. What is the effect size?
A)
5/.85 = 5.88
B)
.85/5 = .17
C)
(5
-
4.4)/.85 = .71
D)
.85/(5
-
4.4) = 1.42
For the following question(s): Professor Juarez thinks the students in her statistics class this term are more creative than most students at this university. A previous study found that students at this university had a mean score of 35 on a standard creativity test. Professor Juarez finds that her class scores an average of 40 on this scale, with an estimated population standard deviation of 7. The standard deviation of the distribution of means comes out to 1.63.
4.
What is the
t
score?
A)
(40
-
35)/7 = .71
B)
(40
-
35)/1.63 = 3.07
C)
(40
-
35)/7
2
= 5/49 = .10
D)
(40
-
35)/1.63
2
= 5/2.66 = 1.88
5.
What effect size did Professor Juarez find?
A)
(40
-
35)/7 = .71
B)
(40
-
35)/1.63 = 3.07
C)
(40
-
35)/7
2
= 5/49 = .10
D)
(40
-
35)/1.63
2
= 5/2.66 = 1.88
6.
If Professor Juarez had 30 students in her class, and she wanted to test her hypothesis using the 5% level of significance, what cutoff
t
score would she use? (You should be able to figure this out without a table because only one answer is in the correct region.)
A)
304.11
B)
1.699.
Assignment 2 Tests of SignificanceThroughout this assignmen.docxkarenahmanny4c
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies. You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables. You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how
every
question should be formatted. You will complete all of the problems. Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses.
All calculations should be coming from your SPSS
. You will need to submit the SPSS output file to get credit for this assignment. This file will save as a .spv file and will need to be in a single file. In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
State your research hypothesis (H
1
) and null hypothesis (H
0
).
Identify your significance level (.05 or .01)
Conduct your analysis using SPSS.
Look for the valid score for comparison. This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’. We will call this “p”.
Compare the two and apply the following rule:
If “p” is < or = significance level, than you reject the null.
Be sure to explain to the reader what this means in regards to your study. (Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable. Perhaps you bold your font or use a different color.
This assignment is due no later than Sunday of Week 6 by 11:55 pm ET. Save the file in the following format: [your last name_SOCI332_A2]. The file must be a word file.
t Tests
t Test for a Single Sample (20 points)
Open SPSS
Enter the number of activities of daily living performed by the depressed clients studied in #1 in the Data View window.
In the Variable View window, change the variable name to “ADL” and set the decimals to zero.
Click Analyze
à
Compare Means
à
One-Sample T test
à
the arrow to move “ADL” to the Variable(s) window.
Enter the population mean (17) in the “Test Value” box.
Click OK.
1.
Researches are interested in whether depressed people undergoing group therapy will perform a different number of activities of daily living after group therapy. The researchers have randomly selected 12 depressed clients to undergo a 6-week group therapy program.
Use the five steps of hypothesis testing to determine whether the average number of activities of daily living (shown below) obtained after therapy is significantly different from a mean number of activities of 17 that is typical for depressed people. (Clearly indicate each step).
Test the difference at the .05 level of significance and at the .01 level (in SPSS this means you change the “confidence level” from 95% to 99%).
As part of Step 5, indicate whether the behavioral scientists should recommend group therapy for all depressed people based.
Chapter 18 – Pricing Setting in the Business WorldThere are few .docxrobert345678
Chapter 18 – Pricing Setting in the Business World
There are few Methods for setting pricing – costs methods vs demand methods
Formulas considering costs and mark up will help you to do the Problem set assignment:
1. Markup for setting prices (Mark up $ = SP-CP); MARK UP % = (MU $/SP) X100)
Formula for setting price with the markup method
SP = Cost/(1- Markup %)
Example - retailer buys A hat for $15 and wants a 40% markup, his selling price would be….
SP = 15/(1-.40)=.60
= $25.00
2. Understand Role of different costs – fixed, variable, total costs and average costs
3. What is the breakeven point? Formula for calculating the Break Even point.
BE = Total Fixed Cost/Fixed cost contribution
Fixed Cost Contribution=Price – variable cost
4. Average Cost = when there are many flavors/types of the same product, producer determines average cost and then add the mark up to set a common selling price.
.ANOVA
Analysis of Variance is a method of testing the equality of three or more population
means by analyzing sample variance.
One-Way ANOVA
The one-way ANOVA is used to compare three or more population means when there is
one factor of interest.
Requirements
The populations have distributions that are approximately normal.
The populations have the same variance.
The samples are simple random samples of quantitative data.
The samples are independent of each other.
The different samples are from populations that are categorized in only one.
way
One-Way ANOVA is a hypothesis test. There are seven steps for a hypothesis test.
Example
A professor at a local University believes there is a relationship between head size and
the major of the students in her biostatistics classes. She takes a random sample of 20
students from each of three classes and records their major and head circumference.
The data are shown in the following table.
Step 1: State the null hypothesis.
Mean 1 equals mean 2 equals mean 3 equals mean 4.
Step 2: State the Alternative hypothesis.
At least one mean is different.
Step 3: State the Level of Significance.
The level of significance is 0.05.
Step 4: State the test statistic.
variance between samples
variance within samples
F
The test statistic follows the F distribution which has two degrees of freedom, one for
the numerator and one for the denominator.
The calculations for the test statistic are complicated, so a software program is
generally used for the calculations. We will be using Microsoft Excel for this example.
Step 5: Calculate
The calculations are done in Microsoft Excel using the data analysis toolpak. Enter the
data into the spread sheet as shown here. Click on data and the data analysis tookpak
button is on the right.
When you click on the button a dialogue box appears.
Choose ANOVA One Factor. Then another dialogue box appears.
Input range is where the data is in the table. Be sure to put a check in the box for labels
in.
Experimental designs and data analysis in the field of Agronomy science by ma...Manoj Sharma
This document discusses experimental design principles and methods for analyzing agricultural data using free online software. It describes the basic principles of randomization, replication, and local control in experimental design. It also outlines different trial types used in extension work like completely randomized design, randomized block design, repeated trials, and surveys. It provides an example of each trial type and describes how to analyze data from one-factor experiments using the OPSTAT online tool, including entering data, running analyses, and interpreting results like critical differences and regression. It recommends other online resources for learning basic statistics and analyzing survey data.
This document provides an overview of quantitative data analysis and statistical tests. It discusses research questions, variables, descriptive and inferential statistics. Common statistical tests are explained like the Mann-Whitney U test, Spearman rank correlation, Kruskal-Wallis test, t-test, Pearson correlation, ANOVA, and chi-square test. Factors to consider when selecting a statistical test are highlighted like level of data, number of groups, independent or related groups, and data distribution. The document emphasizes keeping analyses simple and statistics in context of discussion.
When you are working on the Inferential Statistics Paper I want yo.docxalanfhall8953
When you are working on the Inferential Statistics Paper I want you to format your paper with the following information
I. Introduction – What are inferential statistics and what is the research problem and hypothesis of the article?
II. Methods – Who are the subjects and variables within the article?
III. Results – What is the statistical analysis used, why were these tests chosen? What were the results of these tests and what do they mean?
IV. Discussion – What were the strengths of this article? What would you have done differently in terms of variables and statistical analysis? Why?
V. Conclusion – Reiterate the introduction and include relevant information that answers the questions regarding the hypothesis.
`
Read: Chapter 3 and 4 of Statistics for the Behavioral and Social Sciences.
Participate in One discussion.
Discussion 1 –Standard Normal Distribution– This allows you to look at any data set into the standard distribution form.
Quiz – Hypothesis testing
Submit your Inferential Statics Article Critique – Read Differential Effects of a Body Image Exposure Session on Smoking Urge Between Physically Active and Sedentary Female Smokers. What is the research question and hypothesis? Identify what variables were present, what inferential statistics were used and why, and if proper research methods were used. See grading rubric for full details.
Discussion Post Expectations:
Your initial post (your answer) is due by Day 3 (Thursday) of this week for Discussion 1.
When grading the Standard Normative Distribution discussion I will be looking for your answer to contain:
Week 2 Discussion 1 Board Rubric
Earned
Weight
Content Criteria
0.5
Student identifies and defines what Standard Normative Distribution (SND) is.
Student explains why it is needed to use a SND to compare two data sets.
0.5
Student identifies the purpose of a z-score in a SND.
0.5
Student identifies the purpose of a percentage in a SND.
0.25
Student explains whether a z-score or a percentage does a better job of identifying proportion of a SND.
0.25
The student responds to at least two classmates’ initial posts by Day 7.
1
Student uses correct spelling, grammar and sentence structure.
2
5
Grading - The discussions are both worth a total of 5 points. The breakdown of the grading for this week’s assignment (per discussion assignment) will be as follows:
Posting your answer by the due date (Day 3, Thursday) is worth 4 points. These five points will be based on the information outlined within the Discussion Assignment Expectations. Content will be worth 2 points and format; spelling and grammar will be worth 2 points.
Responding to two of your classmates (for each assignment) is worth 1 point. The answers must be substantive and go beyond “I agree” or “Good job” to qualify for this point.
Intellectual Elaboration:
In Wee.
I need this done ASAP, You have to have SPSS Software on your comput.docxanthonybrooks84958
I need this done ASAP, You have to have SPSS Software on your computer. Please do not request to do the assignment if you don't have the software or if you do not have the understanding to get this assignment complete.
Assignment 2: Tests of Significance
Throughout this assignment you will review mock studies.
You will needs to follow the directions outlined in the section using SPSS and decide whether there is significance between the variables.
You will need to list the five steps of hypothesis testing (as covered in the lesson for Week 6) to see how
every
question should be formatted.
You will complete all of the problems.
Be sure to cut and past the appropriate test result boxes from SPSS under each problem and explain what you will do with your research hypotheses.
All calculations should be coming from your SPSS
.
You will need to submit the SPSS output file to get credit for this assignment.
This file will save as a .spv file and will need to be in a single file.
In other words, you are not allowed to submit more than one output file for this assignment.
The five steps of hypothesis testing when using SPSS are as follows:
State your research hypothesis (H
1
) and null hypothesis (H
0
).
Identify your significance level (.05 or .01)
Conduct your analysis using SPSS.
Look for the valid score for comparison.
This score is usually under ‘Sig 2-tail’ or ‘Sig. 2’.
We will call this “p”.
Compare the two and apply the following rule:
If “p” is < or = significance level, than you reject the null.
Be sure to explain to the reader what this means in regards to your study.
(Ex: will you recommend counseling services?)
* Be sure that your answers are clearly distinguishable.
Perhaps you bold your font or use a different color.
This assignment is due no later than Sunday of Week 6 by 11:55 pm ET.
Save the file in the following format: [your last name_SOCI332_A2].
The file must be a word file.
t Tests
t Test for a Single Sample (20 points)
Open SPSS
Enter the number of activities of daily living performed by the depressed clients studied in #1 in the Data View window.
In the Variable View window, change the variable name to “ADL” and set the decimals to zero.
Click Analyze
Compare Means
One-Sample T test
the arrow to move “ADL” to the Variable(s) window.
Enter the population mean (17) in the “Test Value” box.
Click OK.
Researches are interested in whether depressed people undergoing group therapy will perform a different number of activities of daily living after group therapy. The researchers have randomly selected 12 depressed clients to undergo a 6-week group therapy program.
Use the five steps of hypothesis testing to determine whether the average number of activities of daily living (shown below) obtained after therapy is significantly different from a mean number of activities of 17 that is typical for depressed people. (Clearly indicate each step).
Test the difference at the .05 level of significance a.
Week 6 DQ1. What is your research questionIs there a differen.docxcockekeshia
Week 6 DQ
1. What is your research question?
Is there a difference between the math utility of a male and a female?
2. What is the null hypothesis for your question?
Hn There is no difference in the math utility between male and female.
Alternative hypotheses can also be created in the case the null hypothesis is proven incorrect. Two alternative hypotheses are:
Ha1 Feales have a higher math utility.
Ha2 Males have a higher math utility.
3. What research design would align with this question?
According to Frankfort-Nachmias and Leon-Guerrero (2015) a descriptive research design would be best for this type of study.
4. What comparison of means test was used to answer the question (be sure to defend the use of the test using the article you found in your search)?
The independent-samples T test was used to analyze the means for this data.
5. What dependent variable was used and how is it measured?
The dependent variable is the student’s math utility. It is measured from -3.51 to 1.31(University high school longitudinal study dataset. (2009).
6. What independent variable is used and how is it measured?
Either male (1) of female (2) (University high school longitudinal study dataset. (2009).
7. If you found significance, what is the strength of the effect?
The significance was 0.0000. This is much better than the standard of .05 significance as outlined by Frankfort-Nachmias and Leon-Guerrero (2015).
8. Identify your research question and explain your results for a lay audience, what is the answer to your research question?
My research question was “Is there a difference between the math utility of a male and a female?” Based on the analysis of the means (or average) through testing using the independent-samples T test there was no measurable difference between the math utility of male or females. This leads us to accept the null hypothesis of “There is no difference in the math utility between male and female” as true.
Group Statistics
T1 Student's sex
N
Mean
Std. Deviation
Std. Error Mean
T1 Scale of student's mathematics utility
Male
9453
.0140
1.01962
.01049
Female
9349
-.0481
.97291
.01006
Independent Samples Test
Levene's Test for Equality of Variances
t-test for Equality of Means
F
Sig.
t
df
Sig. (2-tailed)
Mean Difference
Std. Error Difference
95% Confidence Interval of the Difference
Lower
Upper
T1 Scale of student's mathematics utility
Equal variances assumed
17.400
.000
4.276
18800
.000
.06216
.01454
.03367
.09066
Equal variances not assumed
4.277
18775.932
.000
.06216
.01453
.03367
.09065
University high school longitudinal study dataset. (2009).
References
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications.
University high school longitudinal study dataset. (2009). Retrieved from class.waldenu.edu
The t Test for Related Samples
The t Test for Related Samples
Program Transcript
MAT.
A homework assignment for PSYC 354 involves completing several statistical analyses and writing questions. The document provides instructions and data for completing single-sample t-tests, calculating percentiles and effect sizes, and hypothesis testing using z-tests. Students are asked to analyze provided data sets using SPSS and answer conceptual questions related to confidence intervals, statistical power, and descriptive statistics.
Slayter on planning quant design for flc projects - may 2011Elspeth Slayter
The document provides guidance on developing a quantitative research design and data analysis plan for a faculty learning community project. It recommends identifying the research question, goals, objectives and intervention before data collection. It also advises choosing appropriate data collection methods and statistical tests that align with the research question and variables. The document emphasizes preparing "table shells" with planned statistical tests to envision the final data analysis and check that the research design will provide the intended results.
This homework assignment involves completing conceptual questions about statistics, sampling, and probability. It also involves analyzing real data sets in SPSS and interpreting the results. Students are asked to enter data, run analyses including frequencies, descriptive statistics, and graphs. They must interpret the central tendency, dispersion, distribution and outliers of the data. The assignment assesses students' understanding of key statistical concepts and their ability to apply statistical procedures in SPSS and draw conclusions from the results.
Homework 1
Introduction to Statistics
Be sure you have reviewed this module/week’s lesson and presentations before proceeding to the homework exercises. Number all responses. Review the “Homework Instructions: General” document for an example of how homework assignments must look.
Homework 1 does not include any SPSS output and consists only of Part I.
Similar to Psyc 355Education Specialist / snaptutorial.com (20)
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
-------------------------------------------------------------------------------
Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
Psyc 355Education Specialist / snaptutorial.com
1. PSYC 355 Exam 1
For more classes visit
www.snaptutorial.com
Exam 1 Psych 355
3. A p level of 0.05 corresponds to a confidence level of __________%
4. In a within-groups design where one group is measured twice over
time, the appropriate hypothesis test is an:
7. Why do we divide by N-1 rather than by N when estimating a
population standard deviation from the sample standard deviation?
8. The paired-samples t test has three assumptions, including all but:
9. We have learned three t tests, including all of the following except
10. The single-sample t test compares a sample mean to a population
mean when:
12. According to the null hypothesis, the mean difference for the
comparison distribution in a paired-samples t test is:
13. For an independent-samples t test, there were 14 participants in
Group 1 and 17 participants in Group 2. The total degrees of freedom
were:
2. 14. A researcher conducts a single-sample t test and finds statistical
significance at the 0.01 level. The effect size is then calculated and
found to be 0.04. What might you conclude about the findings?
16. In an ______,one sample is compared to a population for which we
only know the mean during hypothesis testing.
22. The critical cutoffs for a two-tailed, paired-samples t test with seven
participants at a p level of 0.01 are:
24. Researchers were interested in whether relaxation training decreases
the number of headaches a person experiences. They randomly assigned
20 participants to a control group or a relaxation training group and
noted the change in number of headaches each group reported from the
week before training to the week after training. The dependent variable
in this study is:
27. A clinical researcher was interested in determining whether his
interventions were effective in minimizing depression symptoms among
his participants. The assess the effectiveness of his treatment program,
he administered a depression inventory prior to his treatment and after
his treatment. He hypothesized that depression scores would lower at a
time two compared to time one. He then compared the mean differences
between the two groups and found that his treatment was effective. The
dependent variable in this study is:
28. To determine our critical values or cutoffs for an independent-
samples t test, we use:
29. The formula H0: U1 = Uz is used to represent the:
30. Following are the results of an independent-samples t test: t(18) = -
2.11, p<0.05. In the current example, the degrees of freedom are:
3. 34. A researcher investigates if the extent to which people care abuot
keeping their house clean and neat changes if they are given new things
in that home. He follows eight families that were selected to receive
home makeovers, assessing their cleanliness before the makeover and
after. Given the following confidence interval [-1.26, 095], make a
decision about the hypothesis.
35. The formula for the null hypothesis for a paired-samples t test is:
36. Unnithan, Houser, and Fernhall (2006) were interested in whether
playing the game DDR affected the heart rate of overweight and
nonoverweight adolescents differently. A group of 22 adolescents, 10
classified as overweight and 12 as not overweight, played DDR for 12
minutes, during which time the researches measured each participants
heart rate. Which statistical test should the researchers use to analyze
their data?
37. The numerator (top portion) of the ratio for calculating all the t
statistics contains:
38. When scientists call a hypothesis test conservative, they mean that it
is:
39. the formula for the degrees of freedom for the dependent-samples t
test is:
40. In a paired-samples test, the comparison distribution of:
**********************
PSYC 355 Lab Project Phase 2: Raw Data
Scoring
4. For more classes visit
www.snaptutorial.com
Instructions
How to Create SPSS Data File
Open a new data file in SPSS. You will create a file containing 1
variable for each item on the survey (for a total of 10). You will score
each individual survey and enter the values into the appropriate column
of the SPSS data file for later analysis.
How to Score Survey and Enter Results into Data File
All questions on the survey except the last one are written as Likert-type
items, with choices ranging from “Strongly agree” to “Strongly
disagree.” In order to enter these into the data file for analysis, each of
the answer choices will be given a corresponding score ranging from 1
to 5. NOTE: It is important to pay attention to the following directions,
as some of the items will be reverse-scored (see below).
1. Gather your completed surveys. It will be necessary to enter data
fromeach individual survey into SPSS. If you have used the online
method, you must follow these steps to access each individual survey:
Sign into your account and go to “My Surveys.” Your survey title will
appear with 3 icons to the right: Design, Collect, and Analyze. Click on
the pie graph under “Analyze.” This will take you to a Response
Summary page.
5. On the menu bar to the left, click on “Browse Responses.” This allows
you to view each individual survey, which is necessary in order to enter
and analyze data in SPSS. Within “Browse Responses,” you can move
from one individual survey to the next by clicking on the “Next” and
“Prev” arrow buttons at the top.
2. All items on the survey will be scored from 1 to 5 except for item 10.
You will enter the scores for each survey into your SPSS data file under
the corresponding variable, case by case. If you have 10 surveys, you
will have 10 cases (rows); if you have 25 surveys, 25 cases (rows), etc.
Scores for items 1, 2, 3, 5, 7, 8, and 9 are as follows:
Strongly agree = 5
Agree = 4
Neither agree nor disagree = 3
Disagree = 2
Strongly disagree = 1
Scores for items 4 and 6 are reversed. This is because, in opposition to
the other items, these items indicate a fundamentally different
worldview than the Christian worldview, so the scoring must be
reversed; this allows higher scores on all items to reflect an
understanding of Christian doctrine, while lower scores indicate
misunderstanding or disagreement. This is a method commonly used in
survey research.
Scores for items 4 and 6 are as follows:
6. Strongly agree = 1
Agree = 2
Neither agree nor disagree = 3
Disagree = 4
Strongly disagree = 5
For item 10, you will simply enter the exact number that the respondent
filled in on the survey (for example, 10 or 63, etc.) under the appropriate
variable in the SPSS data file.
3. Remember that the original research question is about the relationship
between church attendance and understanding of Christian doctrine. We
have one variable that represents church attendance (item 10), but we do
not have one sole variable to compare it to—a total score that represents
doctrinal understanding. Based on what you have learned, how do you
think we should create this variable?
Answer: After you have entered all of your survey data, create a new
variable called Tot_Und (which is shorthand for “total understanding”).
Define this variable as the sum of items 1–9; see Lesson 19 in Green &
Salkind (2011) to review this procedure.
Refer to the “Lab Project Overview and Instructions” in addition to this
document when completing this phase.
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
4.
**********************
7. PSYC 355 Lab Project Phase 3: SPSS Output
For more classes visit
www.snaptutorial.com
Lab Project Phase 3: SPSS Output Instructions
After completing Phase 2 of the Lab Project, you now have 2 important
variables in relation to your research question: a score representing
understanding of Christian doctrine, and a variable representing amount
of church attendance. It is time for you to decide how to analyze the
data! Think about what the research question is asking, and think about
your 2 important variables. Then think about the methods that you have
learned over the past several weeks. Which statistical test is the best
choice for this particular situation? There is a “right” answer to this
question, so think carefully and review your text and notes if necessary.
Once you have decided on which test is the best, you can run the
analysis just as you did in your SPSS homework assignments. You are
required to turn in the output file for your analysis and the related SPSS
generated graph (also covered in SPSS homework assignments). You do
not need to interpret these results, as this will be done in Phase 4 (APA
Results section).
8. Refer to the “Lab Project Overview and Instructions” in addition to this
document when completing this phase.
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
6.
**********************
PSYC 355 SPSS CUMULATIVE ASSESSMENT
For more classes visit
www.snaptutorial.com
SPSS Cumulative Assessment Instructions
The following research questions can be answered using 1 of the 5 tests
you have learned so far: single-sample t-test, paired-samples t-test,
independent-samples t-test, one-way ANOVA, or two-way ANOVA.
Use the information in the tables to construct your SPSS data file, just as
you have been doing in Part 2 of each homework assignment. There is
only 1 correct choice of analysis for each question. The assessment is
open-book/open-notes.
9. For each problem involving a test of significance, your answer must
include: A) the output and an appropriate graph from SPSS; B) a
statistical statement (i.e., t(19) = 1.79, p = .049); and C) a sentence
summarizing the results (i.e., “There was a significant difference
between the two groups on the variable…” or “There was no significant
difference…”).
For ANOVA problems: Report statistical findings and make statements
for all main effects and interaction effects. Use the Fisher LSD test for
any analyses requiring post hoc tests.
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
5.
1. An entrepreneur claims that he has developed a program that can
increase the IQ of adolescent students. To test this claim, a psychologist
administers the WISC (an IQ score for children) to a group of students
before and after completing the training program. Analyze the data to
test the entrepreneur’s claim. (16 pts)
Student
IQ
before
IQ
after
1
2
3
4
103
85
94
106
99
89
90
108
10. 5
6
7
8
9
10
11
12
13
14
15
16
17
18
74
98
83
93
103
96
109
115
86
122
112
126
118
72
74
99
80
99
107
93
111
117
83
122
120
131
116
74
2. The staff at a local psychiatric facility wants to determine whether
implementing a No Smoking rule significantly decreases the length of
stay of inpatients. In order to test this claim, they compared the length of
stay of patients admitted before a No Smoking rule was implemented to
another group of patients admitted after the No Smoking rule was
implemented. Evaluate the claim that the average length of stay was
significantly shorter for the group admitted after the facility
implemented the rule. (16 pts)
11. Smoking
Allowed
No
Smoking
8
5
2
5
8
6
4
14
7
15
12
8
4
13
10
8
5
10
7
8
2
3
2
4
4
8
4
5
2
4
6
7
3. Depressed patients are randomly assigned to 1 of 3 therapists. At
the end of 3 months, each patient completes a standardized test of
depression (higher scores indicate higher level of depression). The
patients’ scores are shown below. Analyze the data to determine how
effective these 3 therapists are at treating depression (assume that before
the treatment, all 3 groups of patients had the same average depression
score). (16 pts)
Therapist Therapist Therapist
12. 1 2 3
35
37
35
37
36
33
39
36
37
37
31
39
35
32
29
32
25
28
33
30
32
4. In light of all the weight loss misinformation and fad diets, a
medical researcher determines to evaluate several of them. She
randomly assigns volunteers (identified as clinically obese) to 1 of 4
diets. She is a firm believer in the benefits of exercise, so she also
assigns them to either the exercise or no exercise group. After 3 months,
she compares the pounds lost for each condition. Was there a significant
effect of the diets and exercise on weight loss? (16 pts)
Exercise
Low
Carb
South
Beach
Adkins
Weight
Watchers
26
28
30
28
22
18
25
21
24
28
28
30
13. 25
20
29 25
26
No
Exercise
15
20
18
18
12
15
15
17
19
28
25
21
34
25
30
28
5. Infants exposed to cocaine in their mother’s womb are thought to
be at high risk for major birth defects. Thirteen infants born to mothers
who are addicted to cocaine are administered the Brazelton Neonatal
Assessment 1 day after birth. For these babies, their scores were as
follows:
Brazelton
Scores
6.25
4.50
8.50
5.50
3.00
14. 7.90
7.50
5.30
6.80
7.50
5.25
7.45
6.80
For the general population, babies normally score an 8.5. Is this group of
babies significantly lower than normal? (16 pts)
**********************
PSYC 355 Week 1 SPSS Homework 1
For more classes visit
www.snaptutorial.com
15. SPSS Homework 1 Instructions
Single-Sample t-Tests and Paired-Sample t-Tests
Part 1:
Note that for all problems in this course, the standard cutoff for a
test of significance will be p < .05 unless otherwise noted in the
problem.
Homework files are found in Blackboard Course Content > Syllabus and
Assignment Instructions > Assignment Instructions > SPSS Homework
1 > SPSS Homework Files (select the particular number for the
module/week you are working on). Always use the Blackboard files
instead of the files on the Green & Salkind website as some files have
been modified for the purposes of this course.
1. Single-Sample t-Test: Based on Green & Salkind - Lesson 22,
Exercises 1–4 (Mod1_Lesson 22 Exercise File 1), but follow the
instructions below instead.
A total score variable is included in the data file in Blackboard
(“tot_score”), so you do not have to compute it. Use this variable as your
dependent variable.
The test value for the single-sample t-test is 2 (1/4 of 8, or the score
which a student would achieve by chance). Use 2 as the test value when
running the analysis for this exercise.
Conduct a single-sample t-test on the total score variable. Paste the
output into your Word document and type in the answers to the
following questions underneath the output: (2 pts for output)
Mean algebra score (2 pts)
t-test value (2 pts)
16. p value (significance) of the test (2 pts)
Write a Results section in current APA style based on your analyses. (3
pts)
Create a histogram that demonstrates the distribution of scores. Be sure
to correctly label the X and Y axes. (3 pts)
2. Green & Salkind: Lesson 23, Exercises 6–8: (Lesson 23, Exercise
File 1)
The following helpful tips are numbered to correspond with the exercise
number to which they refer within the Green & Salkind text:
Instead of identifying these values on your output, as the text states,
write them into your Word file as written answers for #6 a, b, c, and d.
(2 pts for output and 2 pts each for a–d)
All homework “Results sections” must follow the example given in the
Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (4
pts)
You will create the boxplot here instead of in the Results section. (2 pts)
Part 2:
A counseling psychologist administers an interview assessment that
screens for possible internet addiction to his adolescent clients who live
in a rural area. He assumes that children in this area may
exhibit higherscores than children in the general population, who
normally score a 25on a scale of 1–100. The table below shows the
scores the counselor has collected.
17. Using the table, enter the data into a new SPSS file and conduct a
single sample t-test to evaluate whether or not these adolescents
scored higher than the general population.
The steps will be the same as the ones you have been practicing in Part
One of the assignment—the only difference is that you are now
responsible for creating the data file as well. Remember to name and
define your variables under the “Variable View,” then return to the
“Data View” to enter the data.
Paste SPSS output (2 pts)
Write an APA-style Results section based on your analyses. All
homework “Results sections” should follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (3
pts)
Create a histogram that demonstrates the distribution of scores. Be sure
to correctly label the X and Y axes. (2 pts)
2. A clinical psychologist is studying the differences in the number of
Facebook® friends between identical twins raised apart. She believes
that twins raised in different environments will have differences in the
number of friends, which would help point to the influence of
environmental factors over inherited factors on social outcomes. She
divides the twins into two groups (“Twin 1” and “Twin 2”), collects the
data and creates the table below.
Using this table, enter the data into a new SPSS data file and run a
paired-samples t test to test the claim that the identical twins raised
18. apart will have a significantly different number of Facebook®
friends.
The steps will be the same as the ones you have been practicing in Part
One of the assignment—the only difference is that you are now
responsible for creating the data file as well. Remember to name and
define your variables under the “Variable View,” then return to the
“Data View” to enter the data.
a) Paste SPSS output (2 pts)
b) Write a current APA-style Results section based on your analysis. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (2
pts)
c) Create a boxplot comparing the twins’ scores. Be sure to correctly
label the X and Y axes. (2 pts)
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
1.
**********************
PSYC 355 Week 2 SPSS Homework 2
For more classes visit
19. www.snaptutorial.com
SPSS Homework 2 Instructions
Independent Samples t-Tests
Part 1:
Green & Salkind: Lesson 24, Exercises 1–5
The following helpful tips are numbered to correspond with the exercise
number to which they refer:
1. Type these values out underneath your copied and pasted output.
(3 pts)
2. Instead of identifying these values on your output, as the text
states, write them in your Word file as written answers for #2 a, b, and
c. (3 pts, 1 point for each letter)
3. The effect size statistic must be computed by hand (or calculator).
Use the second “easier” formula for d, found in the section on Effect
Size Statistics in this lesson. (3 pts)
4. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (3
pts)
5. Create a boxplot (not an error bar graph) using the following steps
(covered also in Lesson 21). (3 pts)
Go to Graphs > Legacy Dialogs > Boxplot > Select “Simple” > Select
“Summaries for Groups of Cases”
20. Click “Define” and Variable = “Time Spent” (this is your dependent
variable) and Category Axis = “Weight” (this is your independent, or
grouping, variable)
Click OK
Part 2:
1. A learning psychologist is interested in comparing the success of 2
different mnemonics (memorization methods) on performance in a
memory task. He assigns students to two groups, one which learns and
uses a language-based rhyming memory technique, and one which learns
and uses a visual “method of loci” spatial memory technique. He then
administers a memory task to each group of students. The students are
scored based on the percentage of correct answers. Using the table
below, enter the data into a new SPSS data file and use an
independent-samples t test to analyze the claim that the two
mnemonic styles are different.
The steps will be the same as the ones you have been practicing in Part 1
of the assignment—the only difference is that you are now responsible
for creating the data file as well. Remember to name and define your
variables under the “Variable View,” then return to the “Data View” to
enter the data. (3 for output)
Table is shown on following page.
Language-
Based
82
89
67
94
21. 76
63
89
84
93
Spatially-
Based
93
78
99
87
78
62
87
91
95
2. Create a boxplot illustrating the differences between the two methods
of language learning. (3)
3. Write a current APA-style Results section based on your analyses. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
22. Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (4)
Part 3: Cumulative Homework
1. The effects of a new faith-based anxiety treatment program are
studied in a group of elderly patients with Generalized Anxiety Disorder
(GAD). One of the outcome measures is the Geriatric Anxiety Inventory
(GAI) (Pachana et al., 2007), a measure with possible scores from 0–20,
with higher scores indicating higher anxiety. A large group of elderly
patients completed the GAI before treatment. Fifteen patients with GAI
scores of 10 or higher were chosen to participate in the study. The
patients underwent the treatment program and completed the GAI at the
end of treatment. The scores are listed below. Do the elderly patients
exhibit lessened anxiety, as demonstrated by their GAI scores, after
participating in the faith-based treatment program? Choose the correct
test to analyze this question, set up the SPSS file, and run the analysis.
Follow the directions under the table below.
GAI Score
Before
Treatment
GAI Score
After
Treatment
10
12
17
13
10
7
11
12
14
9
23. 13
16
11
11
15
18
11
11
14
15
10
12
11
13
13
17
9
13
10
12
1. Paste appropriate SPSS output. (5)
2. Paste appropriate SPSS graph. (5)
3. Write a current APA-style Results section based on your analyses.
All homework “Results sections” should follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (5)
This assignment is due by 11:59 p.m. (ET) on Monday of Module/Week
2.
**********************
24. PSYC 355 Week 3 SPSS Homework 3
For more classes visit
www.snaptutorial.com
SPSS HOMEWORK 3 INSTRUCTIONS
ONE-WAY ANOVA
Part 1:
Green & Salkind: Lesson 25, Exercises 1–3
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. Use Tukey’s test as the post hoc test for ANOVAs in PSYC 355. Be
sure to check this box when you run analyses. For letters a–d, instead of
identifying these values on your output, as the text states, write them
into your Word file as written answers for #1 a, b, c, and d. (2 pts for
output and 2 pts each for a–d)
2. ---------- (3 pts)
25. 3. Remember to put your dependent variable in the “variable” box, and
your independent, or grouping, variables in the “category axis” box. (3
pts)
Part 2:
1. Twenty-four adults who have been diagnosed with social anxiety
disorder are randomly assigned to one of 3 group therapy conditions in
order to improve their social skills: manualized cognitive-behavioral
therapy (MCBT), non-manualized cognitive-behavioral therapy
(NMCBT), and talk therapy (T). Following two months of therapy, the
participants are assessed on a standardized measure of social skills. On
this instrument, scores range from 0–45, and higher scores indicate
better or improved social skills, while lower scores indicate social skills
that need improvement. These scores are shown in the table
below. Conduct a one-way ANOVA to determine how effective these
3 therapy conditions are at improving social skills.
The steps will be the same as the ones you have been practicing in Part 1
of the assignment—the only difference is that you are now responsible
for creating the data file as well. Remember to name and define your
variables under the “Variable View,” then return to the “Data View” to
enter the data. (3)
MCBT
29, 32, 26, 33, 32,
37, 30, 38
NMCBT 31, 30, 28, 26, 31,
26. 27, 29, 27
T
25, 20, 24, 26, 26,
30, 27, 25
2. What is the F ratio for the therapy group main effect? (3)
3. What is the effect size for the overall effect of therapy type on social
skills scores? According to general conventions, is this effect small,
medium, or large? (3)
4. Write a current APA-style Results section based on your analyses. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (3)
Part 3: Cumulative Homework
1. A researcher wanted to investigate whether there was a difference in
satisfaction ratings in an assisted living facility between residents who
had a plant to take care of vs. those who did not have a plant. Due to
relocations during the study, 3 participants were dropped from the “No
Plant” group. The researcher then administered a scale asking them to
rate their overall satisfaction with the facility. Did having a plant have an
impact on the residents’ overall satisfaction levels? Choose the correct
test to analyze this question, set up the SPSS file, and run the analysis.
Follow the directions under the table below (on next page).
28. 28
25
40
1. Paste appropriate SPSS output. (4)
2. Paste appropriate SPSS graph. (4)
3. Write a current APA-style Results section based on your analyses.
All homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (4)
This assignment is due by 11:59 p.m. (ET) on Monday of Module/Week
3.
PSYC 355 Week 4 SPSS Homework 4
http://www.snaptutorial.com/PSYC-355/product-29894-PSYC-
355-Week-4-SPSS-Homework-4-
For more classes visit
29. www.snaptutorial.com
SPSS Homework 4 Instructions
Two-Way ANOVA
Part One:
Note: For the two-way ANOVA, you will be expected to create a line
graph as covered in the SPSS tutorial in the Course Content (and
not a boxplot as in the textbook). This applies to future cumulative
questions as well.
Green & Salkind: Lesson 26, Exercises 1, 4, 5, 6, 7, and 8
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. Instead of identifying these values on your output, as the text states,
please write them into your Word file as written answers for #1 a, b, c,
and d. (2 pts for output; a-d = 2 pts each)
4. Produce a line graph instead of a boxplot for this problem. Follow
directions in course SPSS tutorial for setting up a line graph. (2 pts)
5. ------- (2 pts)
6. ------- (2 pts)
7. All homework “Results sections” should follow the example given in
the Course Content document “Writing Results of Statistical Tests in
APA Format” (note: you do not have to refer to a figure). (2 pts)
30. 8. Produce a line graph instead of a boxplot for this problem. Follow
directions in course SPSS tutorial for setting up a line graph. (2 pts)
Part Two:
1. A health psychologist is interested in the effects of exercise on stress
in people who regularly exercise. Specifically, she is interested in the
type of exercise as well as the time of day that the individual exercises.
She recruits participants from a local health club who regularly
participate in one of three types of exercise: swimming, aerobics, and
tennis. She further divides these participants by whether they exercise in
the morning or the evening. She then administers a questionnaire to each
individual assessing their self-reported stress level. (HIGHER SCORE =
HIGHER STRESS). Conduct a two-way ANOVA to analyze these data.
Use Tukey’s test in order to conduct any necessary post hoc analyses if
there are significant main effects. You do not have to follow up on
significant interactions at this time.
The steps will be the same as the ones you have been practicing in Part
One of the assignment—the only difference is that you are now
responsible for creating the data file as well. Remember to name and
define your variables under the “Variable View,” then return to the
“Data View” to enter the data.
Morning
Swimming AerobicsTennis
10
16
12
19
21
16
17
21
18
31. 16
9
18 14
Evening
14
13
8
12
12
17
12
14
9
10
12
15
19
14
1. SPSS output (2 pts, -1 pt if no post hoc test)
2. Write a current APA-style Results section based on your analyses. All
homework “Results sections” should follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis.For
the two-way ANOVA, be sure to include statistical statements
concerning the F ratios and p values for both main effects and the
interaction, and interpretation statements about all 3 of these effects. (2)
3. Is there a significant interaction effect? (2)
4. Based on your results, is there one type of exercise that seems more
effective in reducing stress than the others? Remember that higher
scores = higher stress. (2)
Part 3: Cumulative Homework
32. 1. An investigator in child development research is studying whether
parenting styles have an effect on second grade students’ behavior at
school. She interviews 25 volunteer families from the same class and
separates them into three groups of parenting styles: authoritarian (n =
8); authoritative (n = 8); and permissive (n = 7). Their teacher fills out a
behavior inventory for each of the 25 children, and the investigator
collects and scores them. The scores are contained in the table below.
The scores can range from 0–20, and a higher score indicates more
behavior problems. Is there a significant difference between the groups?
Choose the correct test to analyze this question, set up the SPSS file, and
run the analysis. Follow the directions under the table below.
Authoritarian
8, 13, 4, 6, 5, 4,
9,12,
Authoritative
8, 5, 6, 4, 2, 5, 10,
13
Permissive
10, 8, 11, 9, 8, 3,
15
Paste appropriate SPSS output. (4)
Paste appropriate SPSS graph. (4)
33. Write a current APA-style Results section based on your analyses. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (4)
PSYC 355 Week 5 SPSS Cumulative Assessment
http://www.snaptutorial.com/PSYC-355/product-29895-PSYC-
355-Week-5-SPSS-Cumulative-Assessment
For more classes visit
www.snaptutorial.com
SPSS Cumulative Assessment Instructions
The following research questions can be answered using 1 of the 5 tests
you have learned so far: single-sample t-test, paired-samples t-test,
independent-samples t-test, one-way ANOVA, or two-way ANOVA.
Use the information in the tables to construct your SPSS data file, just as
you have been doing in Part 2 of each homework assignment. There is
only 1 correct choice of analysis for each question, and note that
some tests are 1-tailed and some are 2-tailed. The assessment is open-
book/open-notes.
34. For each problem involving a test of significance, your answer must
include: A) SPSS output; B) an appropriate graph from SPSS; C) a
Results section in current APA style including a statistical statement
(i.e., t(19) = 1.79, p = .049); a sentence summarizing the results “in
English” (i.e., “There was a significant difference between the two
groups on the variable…” or “There was no significant difference…”);
and a decision about the null hypothesis.
For ANOVA problems: Report statistical findings and make statements
for all main effects and interaction effects. Use Tukey’s test for any
analyses requiring post hoc tests.
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
5.
1. Children who experience chronic pain as a result of medical
procedures are the focus of a psychiatrist’s study. Specifically, the
psychiatrist wants to measure whether a new program helps decrease
feelings of chronic pain in the short-term. He measures children’s self-
reports of pain levels before treatment on a standardized scale with a
range of 0–10, with 10 being the most severe. He then administers the
new program, and measures children’s pain levels after treatment. Does
the new treatment decrease self-reported levels of chronic pain? (16 pts)
2. A health psychologist in a northern climate wants to evaluate the
claim that UV lamps help lower depressive symptoms in middle-aged
women. She recruits volunteers who meet the criteria for clinical
depression and assigns them to two groups: one group receives a
standard treatment for depression and undergoes a half hour of UV lamp
therapy each day; the other group receives the same standard treatment
for depression but without UV lamp therapy. At the end of two months,
she administers a depression inventory where lower scores indicate
35. fewer depressive symptoms (lower levels of depression). Assume all
other variables are controlled for in the study. Evaluate the claim that
depression treatment plus the UV lamp results in lower depression
scores than depression treatment alone. (16 pts)
3. As part of a new prevention program, a clinical psychologist wants to
see whether feelings of alienation differ as a function of immigration
status in a local high school. She divides volunteer students into three
categories: first-generation immigrants, second-generation immigrants,
and non-immigrants. She then administers an instrument assessing
feelings of alienation, where higher scores indicate stronger feelings of
alienation from peers, adults, and society in general. Is there a difference
in alienation scores among these three groups? (16 pts)
4. In response to media reports of violence on college campuses, a
psychologist who works at a local community college decides to study
students’ perceptions of campus safety. He hopes to use these results to
help develop an on-campus violence prevention program. The
administration has asked him additionally to look at whether perceptions
of safety differ depending on students’ year in school and gender. The
psychologist administers a questionnaire with possible scores ranging
from 1–70, with higher scores indicating higher perceptions of safety on
campus, and lower scores indicating perceptions that the campus is less
safe. Based on the data collected below, do year in school and/or gender
have an effect on perceptions of campus safety? (16 pts)
5. A cross-cultural psychologist living in an overseas, non-Western rural
area has a background studying culture bias in traditional psychological
testing procedures. She contends that members of a rural community
who normally score lower than average on traditional Western-style IQ
tests will score better than the general population on a new test that
emphasizes practical and social intelligence. Scores on the test can range
36. from 1-100. She recruits 18 volunteers and administers the new test.
Their scores are as follows:
**********************
PSYC 355 Week 5 SPSS Homework 5
For more classes visit
www.snaptutorial.com
SPSS HOMEWORK 5 INSTRUCTIONS CORRELATION
Part 1:
Green & Salkind: Lesson 31, Exercises 1–4
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. ---------- (2 pts for output and 2 pts each for a–c)
2. Answer this question in sentence form. Include the correlation (r) and
degrees of freedom, the p value, and whether these values indicate a
significant correlation between the variables or not. (2 pts)
3. All homework “Results sections” must follow the example given in
the Course Content document “Writing Results of Statistical Tests in
37. Current APA Format” (Note: you do not have to refer to a figure). (2
pts)
4. ---------- (2 pts)
Part 2:
1. A clinical psychologist would like to determine whether there is a
relationship between observer ratings of children’s externalizing
behaviors and scores on an established diagnostic interview assessing
externalizing disorders (like ADHD, CD, etc.). He administers the
diagnostic interview to 28 children and records these scores. He then
trains an observer to independently rate carefully-defined externalizing
behaviors for each of the 28 children. These scores are totaled for an
overall “externalizing behavior index.” On both the interview and the
behavioral ratings, a higher score indicates higher levels of externalizing
behavior. These scores are listed in the table below. Conduct a Pearson
correlation coefficient analysis to determine whether there is a
relationship between the interview scores and behavioral ratings for this
group of children.
The steps will be the same as the ones you have been practicing in Part
One of the assignment—the only difference is that you are now
responsible for creating the data file as well. Remember to name and
define your variables under the “Variable View,” then return to the
“Data View” to enter the data
a) SPSS output (2 pts)
b) Create a simple scatterplot of the relationship between these variables
(define interview scores as the x-axis and behavioral ratings as the y-
axis). (2)
38. c) Write a current APA-style Results section based on your analyses. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. For a
correlation analysis, also be sure to include the direction of the
relationship between the variables (positive? negative? none?) in your
section. (2)
2. A neuropsychologist is assessing the relationship between brain
function and performance on a visuo-spatial task. He administers a test
to 14 patients on which scores can range from 1 to 20: a high score
indicates normal brain function, and a low score indicates some levels of
brain dysfunction. He then asks each patient to complete a maze and
records the number of mistakes the patient makes from start to finish.
The scores are listed in the table below. Conduct a Pearson correlation
coefficient analysis to determine what the relationship is, if any, between
brain function and performance on the maze task.
The steps will be the same as the ones you have been practicing in Part 1
of the assignment—the only difference is that you are now responsible
for creating the data file as well. Remember to name and define your
variables under the “Variable View,” then return to the “Data View” to
enter the data.
a) SPSS output (2)
b) Create a simple scatterplot of the relationship between these variables.
(2)
c) Write a current APA-style Results section based on your analyses. All
homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
39. Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. For a
correlation analysis, also be sure to include the direction of the
relationship between the variables (positive? negative? none?) in your
section. (2)
Part 3:
Cumulative Homework
1. A developmental psychologist is studying whether students in a
certain preschool program perform better than preschoolers in the state
in general on a measure of reading readiness. The mean score for
preschoolers in the state on the measure is 83. The psychologist tests the
preschoolers in the program and records the scores in the table below.
Choose the correct test to analyze this question, set up the SPSS file, and
run the analysis. Follow the directions under the table below
a) Paste appropriate SPSS output. (3)
b) Paste appropriate SPSS graph. (2)
c) Write an APA-style Results section based on your analyses. All
homework “Results sections” should follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (3)
2. In a study of the relationship between girls’ playtime activities and
self-esteem, 16 girls in a fourth-grade class are selected and randomly
assigned to one of two groups. One group plays with a selection of
40. Barbie™ dolls for one hour, and the other group plays with a selection
of toy animal figures. At the end of the hour, the girls are given a verbal
interview designed to measure self-esteem. Scores range from 1–12, and
higher scores = higher feelings of self-esteem. Is there a significant
difference between the groups on feelings of self-esteem? Choose the
correct test to analyze this question, set up the SPSS file, and run the
analysis. Follow the directions under the table below.
a) Paste appropriate SPSS output. (2)
b) Paste appropriate SPSS graph. (2)
c) Write an APA-style Results section based on your analyses. All
homework “Results sections” should follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. 2)
This assignment is due by 11:59 p.m. (ET) on Monday of Module/Week
5.
**********************
PSYC 355 Week 6 SPSS Homework 6
For more classes visit
www.snaptutorial.com
41. SPSS Homework 6 Instructions
Prediction: Bivariate Linear Regression
Part 1:
Note: The z-scoring method used in the practice data file is covered in
Lesson 19 during PSYC 354.
Green & Salkind: Lesson 33, Exercises 1, 3–4
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. Though the example in the lesson includes creating a z score
variable, this step is not necessary for the homework exercises. (3 pts for
output and 3 pts each for a–e)
2. Write the answer to the last part of this question beneath your
graph, in sentence form. (3 pts)
3. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a
figure). Note: The statistical statement for a bivariate linear
regression must include at least the equation of the line and the
confidence interval for the slope (the second row under Confidence
Intervals in the output). (3 pts)
Part 2:
42. 1. A community psychologist is interested in whether spending time
in after-school programs is predictive of the number of arrests as a
young adult in a high-risk neighborhood. After collecting records on 17
individuals over 8 years, the psychologist compiles the information
listed in the table below. Conduct a linear regression to analyze the
research question.
The steps will be the same as the ones you have been practicing in Part 1
of the assignment—the only difference is that you are now responsible
for creating the data file as well. Remember to name and define your
variables under the “Variable View,” then return to the “Data View” to
enter the data. (3 pts)
Table is shown on the following page.
Hours
Spent in
After-
School
Programs
Number of
Arrests
After Age
17
3 2
41 1
68 1
43. 29 0
7 5
12 4
121 0
54 1
19 3
134 0
106 1
67 1
25 3
73 1
38 4
110 0
31 3
2. Construct a scatterplot of the relationship between the 2 variables.
Plot the regression line on this graph. (3 pts)
3. Is time spent in after-school programs predictive of the number of
arrests as a young adult? Write a Results section in current APA style
describing the outcome. All homework “Results sections” must follow
the example given in the Course Content document “Writing Results of
44. Statistical Tests in Current APA Format” (Note: you do not have to refer
to a figure). The statistical statement for a bivariate linear regression
must include at least the equation of the line and the confidence
interval for the slope (the second row under Confidence Intervals in
the output). (3 pts)
Part 3: Cumulative Homework
1. To investigate the relationship between hours spent studying and
exam scores, researchers measured the following. Is there a significant
relationship between hours spent studying and scores? Choose the
correct test to analyze this question, set up the SPSS file, and run the
analysis. Follow the directions under the table on the following page.
Hours
Spent
Studying
Exam
Scores
1
3
3
4
4
5
40
50
51
61
73
71
45. 5
5
6
6
7
7
8
64
75
68
76
94
85
84
1. Paste appropriate SPSS output. (3 pts)
2. Paste appropriate SPSS graph. (3 pts)
3. Write a Results section in current APA style describing the
outcome. All homework “Results sections” must follow the example
given in the Course Content document “Writing Results of Statistical
Tests in Current APA Format” (Note: you do not have to refer to a
figure). (4 pts)
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
6.
**********************
For more classes visit
46. www.snaptutorial.com
SPSS Homework 7 Instructions
Chi Square
Part 1:
Green & Salkind: Lesson 40, Exercises 1–4
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. Use the method reviewed in the presentation to weight the cases
for this data set. (no points—done in data file)
2. Do a, b, and c. (2 pts for output and 2 pts each for a–c)
3. ---------- (2 pts)
4. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (2
pts)
Green & Salkind: Lesson 41, Exercises 1–3
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
47. NOTE: This exercise does not use the weighted cases method. Use the
data file “as is.”
1. Do a, b, c, d, and e. For letter “e,” this question is asking
specifically about effect size. (2 pts for output and 2 pts each for a–e)
2. ---------- (2 pts)
3. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (2
pts)
Part 2:
1. An industrial/organizational (I/O) psychologist is helping a company
determine the type of work stations preferred by its employees. The
business owner believes that people who work in different departments
may prefer different work station layouts. In order to examine this claim,
the I/O psychologist sets up 3 simulated work stations: private office
(PO), semi-private office (SPO), and open floor plan (OFP). She recruits
employees from 3 different departments: Information Technology,
Human Resources, and Marketing. The participants spend 30 minutes in
each simulated work station performing general pre-arranged tasks. At
the end of the 1.5 hours, the participants turn in a form on which they
mark which work station they prefer. The results are listed in the table
on the following page. Perform a chi square test of independence
(using an SPSS two-way contingency table analysis) to determine
whether the proportions of work station preferences differ across
departments. Use the weighted cases method.
The steps will be the same as the ones you have been practicing in Part 1
of the assignment—the only difference is that you are now responsible
48. for creating the data file as well. Remember to name and define your
variables under the “Variable View,” then return to the “Data View” to
enter the data. (2 pts)
Private
Office
Semi-
Private
Office
Open
Floor
Plan
TOTAL
Information
Technology
9 6 4 19
Human
Resources
6 10 3 19
Marketing 7 3 9 19
TOTAL 22 19 16 57
2. Create a clustered bar graph depicting your results. (2 pts)
3. Write an APA-style Results section describing the outcome. All
homework “Results sections” must follow the example given in the
Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (2
pts)
Part 3: Cumulative Homework
1. A researcher wants to find out if the number of absences from a
chemistry class are predictive of final exam scores at a local university.
The data from the past term are in the table below. Are number of
absences predictive of final exam scores? Choose the correct test to
49. analyze this question, set up the SPSS file, and run the analysis. Follow
the directions on the following page.
Number
of
Absences
Final
Exam
Scores
1
1
2
3
4
5
5
5
6
6
6
7
7
98
95
89
89
80
85
80
75
76
69
70
62
60
1. Paste appropriate SPSS output. (2 pts)
50. 2. Paste appropriate SPSS graph. (2 pts)
3. Write an APA-style Results section describing the outcome. All
homework “Results sections” must follow the example given in the
Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (2
pts)
Submit this assignment by 11:59 p.m. (ET) on Monday of Module/Week
7.
**********************
PSYC 355 Week 8 SPSS Homework 8
For more classes visit
www.snaptutorial.com
SPSS Homework 8 Instructions
Nonparametric Tests
51. Part 1:
1. Green & Salkind: Lesson 42, Exercises 1, 3–4
The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. This research scenario will be familiar to you. Do letters a, b, and
c, answering the questions beneath your SPSS output. (3 pts for output
and 2 pts each for a–c)
2. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (4
pts)
3. Create a boxplot as done in earlier modules/weeks. (3 pts)
2. Spearman Rho Exercise: This exercise is not found in Green &
Salkind. Open the data file “Mod8_SpearmanRho_Exercise File” in the
Module/Week 8 SPSS Assignments folder in Blackboard and read the
following information; answer the questions below.
52. Scenario: During the Vietnam War, a draft was put in place that selected
young men born on certain dates and placed them in the armed services.
The process proceeded via lottery: Dates like “Sept. 14” were placed in
capsules, one for each of the 365 days of the year, and the capsules were
then drawn randomly from a container. In the 1970 draft, Sept. 14 was
the first date drawn, meaning that all young men born on Sept. 14 were
eligible for the very first round of the draft, and so on. After the results
of the 1970 draft were analyzed, many statisticians and politicians
asserted that the process had not been random at all, and certain men had
a higher chance of being drafted than others. This case is famous,
making it to the pages of international newspapers and the U.S. Supreme
Court.
In the SPSS data file in Blackboard, you will find the original 1970 draft
data with two variables. Column 1 contains the consecutive day of the
year (1 = Jan. 1; 2 = Jan. 2; and so on). Column 2 contains the draft rank
(1 = first date drawn; 2 = second date drawn; and so on). So, in the first
row of the data set, Day 1 (Jan. 1) had a draft rank of 305. The lower the
draft rank, the sooner and more likely a man was to be drafted. So, a
higher rank (like 305, for example) was preferable to those who did not
want to be drafted right away.
If the process had been statistically random, there would be no
correlation between the day of the year you were born and the rank that
was assigned to you (r = 0). Any type of significant correlation would
mean that there was something relating the variables beyond mere
random error, or chance.
53. 1. Open the data file and perform a Spearman correlation analysis for the
day of year and the draft rank. Paste your output in the homework
document. (2 pts)
2. Write a current APA-style results section describing the outcome. (2
pts)
3. Answer the next two questions in “layman’s terms” as if for someone
who does not know much about statistics: (a) Why did people accuse the
process of not being random? (b) What do the data indicate for men born
earlier in the year vs. men born later in the year? (2 pts)
It’s not required, but if you want to check out the original New York
Times article and see an interesting graph
Part 2:
1. A university assessment department collects data to determine
whether class ranking differs between male and female students. Based
on the top 12 males and top 12 females of the senior class, is there a
difference between genders on where they are ranked in their class?
Perform a Mann-Whitney U test, being sure to follow the directions on
the following page. (3 pts)
58. Note: Your file must be set up in the same manner as the example data
file and the exercise file from Part 1 with a grouping variable and a
dependent/test variable. Because these are class rankings, they are
ordinal data and must be identified as such in “Variable View” under the
column “Measure.” Click in the cell under “Measure” in the row for
your class rank variable and choose “Ordinal.” This ensures that SPSS
treats the data at the proper level of measurement.
2. Create a boxplot depicting the results. (3 pts)
3. Write a current APA-style results section describing the outcome. All
homework “results sections” must follow the example given in the
Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (3
pts)
Part 3: Cumulative Homework
1. An organizational psychologist wants to find out if job satisfaction
ratings differ as a function of department (human resources, sales, and
research and development) and/or time of shift (early, late). Choose the
59. correct test to analyze this question, set up the SPSS file, and run the
analysis. Follow the directions under the table below.
Early shift
Human Resources
Sales
Research and Development
10
16
12
16
9
62. 12
15
19
14
1. Paste appropriate SPSS output. (3 pts)
2. Paste appropriate SPSS graph. (3 pts)
3. Write a current APA-style results section describing the outcome.
All homework “results sections” must follow the example given in the
Course Content document “Writing Results of Statistical Tests in
63. Current APA Format” (Note: you do not have to refer to a figure). (3
pts)
Submit this assignment by 11:59 p.m. (ET) on Friday of Module/Week
8.
**********************
PSYC 355 Week 8 SPSS HomeWork
For more classes visit
www.snaptutorial.com
SPSS Homework 8 Instructions
Nonparametric Tests
Part 1:
1. Green & Salkind: Lesson 42, Exercises 1, 3–4
64. The following helpful tips are numbered to correspond with the exercise
number to which they refer (a dash indicates that no tips are needed):
1. This research scenario will be familiar to you. Do letters a, b, and
c, answering the questions beneath your SPSS output. (3 pts for output
and 2 pts each for a–c)
2. All homework “Results sections” must follow the example given
in the Course Content document “Writing Results of Statistical Tests in
Current APA Format” (Note: you do not have to refer to a figure). (4
pts)
3. Create a boxplot as done in earlier modules/weeks. (3 pts)
2. Spearman Rho Exercise: This exercise is not found in Green &
Salkind. Open the data file “Mod8_SpearmanRho_Exercise File” in
the Module/Week 8 SPSS Assignments folder in Blackboard and
read the following information; answer the questions below.
Scenario: During the Vietnam War, a draft was put in place that selected
young men born on certain dates and placed them in the armed services.
The process proceeded via lottery: Dates like “Sept. 14” were placed in
capsules, one for each of the 365 days of the year, and the capsules were
then drawn randomly from a container. In the 1970 draft, Sept. 14 was
the first date drawn, meaning that all young men born on Sept. 14 were
eligible for the very first round of the draft, and so on. After the results
of the 1970 draft were analyzed, many statisticians and politicians
asserted that the process had not been random at all, and certain men had
65. a higher chance of being drafted than others. This case is famous,
making it to the pages of international newspapers and the U.S. Supreme
Court.
In the SPSS data file in Blackboard, you will find the original 1970 draft
data with two variables. Column 1 contains the consecutive day of the
year (1 = Jan. 1; 2 = Jan. 2; and so on). Column 2 contains the draft rank
(1 = first date drawn; 2 = second date drawn; and so on). So, in the first
row of the data set, Day 1 (Jan. 1) had a draft rank of 305. The lower the
draft rank, the sooner and more likely a man was to be drafted. So, a
higher rank (like 305, for example) was preferable to those who did not
want to be drafted right away.
If the process had been statistically random, there would be no
correlation between the day of the year you were born and the rank that
was assigned to you (r = 0). Any type of significant correlation would
mean that there was something relating the variables beyond mere
random error, or chance.
1. Open the data file and perform a Spearman correlation analysis for
the day of year and the draft rank. Paste your output in the homework
document. (2 pts)
2. Write a current APA-style results section describing the outcome.
(2 pts)
3. Answer the next two questions in “layman’s terms” as if for
someone who does not know much about statistics: (a) Why did people
66. accuse the process of not being random? (b) What do the data indicate
for men born earlier in the year vs. men born later in the year? (2 pts)
It’s not required, but if you want to check out the original New York
Times article and see an interesting graph,
Part 2:
1. A university assessment department collects data to determine
whether university rankings differ based on their regional location.
Some rankings are missing because the universities ranked at that level
were in different regions than those of interest to the department. Based
on eight universities in each of two different regions, is there a
difference between university rankings based on their regional
locations? Perform a Mann-Whitney U test, being sure to follow the
directions under the table. (3 pts)
West
Coast
East
Coast
2
5
6
12
16
1
3
4
7
8
67. 17
18
19
10
13
15
Note: Your file must be set up in the same manner as the example data
file and the exercise file from Part 1, with a grouping variable and a
dependent/test variable. Because these are rankings, they are ordinal data
and must be identified as such in “Variable View” under the column
“Measure.” Click in the cell under “Measure” in the row for your
university rank variable, and choose “Ordinal.” This ensures that SPSS
treats the data at the proper level of measurement.
2. Create a boxplot depicting the results. (3 pts)
3. Write a current APA-style Results section based on your analyses.
All homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (3
pts)
68. Part 3: Cumulative Homework
1. A political pollster is curious about the effects of a town hall
meeting on people’s intentions to support a state proposition that would
legalize gambling. He interviews people as they leave and asks them
whether their opinion about the proposition has changed as a result of
the meeting. He records these frequencies in the table below. Choose the
appropriate test to analyze this data, and follow the directions below the
table.
Less likely to
support
No
change
More likely to
support
25 12 9
1. Paste appropriate SPSS output. (3 pts)
2. Paste appropriate SPSS graph. (3 pts)
3. Write a current APA-style Results section based on your analyses.
All homework “Results sections” must follow the example given in the
SPSS tutorials and the Course Content document “Writing Results of
Statistical Tests in APA Format” (note: you do not have to refer to a
figure). Remember to include a decision about the null hypothesis. (3
pts)
69. Submit this assignment by 11:59 p.m. (ET) on Friday of Module/Week
8.
**********************