5) look up the following health-based peer-reviewed journal article .pdf

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5) look up the following health-based peer-reviewed journal article that displays a frequency distribution or histogram in the results section González-Villalpando, C., Dávila-Cervantes, C. A., Zamora-Macorra, M., Trejo-Valdivia, B., & González-Villalpando, M. E. (2014). Risk factors associated to diabetes in Mexican population and phenotype of the individuals who will convert to diabetes. salud pública de méxico, 56(4), 317-322. a) Describe the characteristics of the grouped data in this journal article. b) What additional ways can the group data may be displayed for publication? What is the rationale for selecting these alternative methods? Method of Display Rationale Method of Display Rationale Solution The given quation deals with the study of the research paper results. a. The grouped data shown in the result of the paper is, the number of people, male and female in the converter and non-converter heads on various variables, such as mother,father,brother,their weight and many other variables.The studied variables are all quantitative variables. b. The grouped data can be displayed using, i. pie chart representation, since in this type of represenatation one can at a glance get an overall idea about the reatio or percentage of the people under each head. ii. frequency polygon, since it would also give a crude idea about the relationship between the variable under study and the frequency of the variable under each head. iii. ogive representation, since it would additionally give a trend of the variables under study, and help to estimate or predict the variable value at any point under study. iv. boxplot representation, since it would give an idea about the median of the variables under study and also give an idea about the presence of any possible outliers and also the quartiles. and many more such echniques can be applied depending on the requirement of the research needs..

and many more such echniques can be applied depending on the requirement of the research
needs.

https://qidiantiku.com/solution-manual-for-statistics-informed-decisions-using-data-5th-edition-by-michael-sullivan.shtml Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solution manual.pdf name：Solution manual for Statistics: Informed Decisions Using Data 5th edition by Michael Sullivan Edition：5th edition author：by Michael Sullivan III ISBN：ISBN-10 ‏ : ‎ 0134135377 ISBN-13 ‏ : ‎ 9780134135373 type：solution manual format：word/zip All chapter include

2020-l1-s3.pdf

MariamAlraeesi

CHAPTER 8 QUANTITATIVE METHODSWe turn now from the introductio

JinElias52

CHAPTER 8 QUANTITATIVE METHODS We turn now from the introduction, the purpose, and the questions and hypotheses to the method section of a proposal. This chapter presents essential steps in designing quantitative methods for a research proposal or study, with specific focus on survey and experimental designs. These designs reflect postpositivist philosophical assumptions, as discussed in Chapter 1. For example, determinism suggests that examining the relationships between and among variables is central to answering questions and hypotheses through surveys and experiments. In one case, a researcher might be interested in evaluating whether playing violent video games is associated with higher rates of playground aggression in kids, which is a correlational hypothesis that could be evaluated in a survey design. In another case, a researcher might be interested in evaluating whether violent video game playing causes aggressive behavior, which is a causal hypothesis that is best evaluated by a true experiment. In each case, these quantitative approaches focus on carefully measuring (or experimentally manipulating) a parsimonious set of variables to answer theory-guided research questions and hypotheses. In this chapter, the focus is on the essential components of a method section in proposals for a survey or experimental study. DEFINING SURVEYS AND EXPERIMENTS A survey design provides a quantitative description of trends, attitudes, and opinions of a population, or tests for associations among variables of a population, by studying a sample of that population. Survey designs help researchers answer three types of questions: (a) descriptive questions (e.g., What percentage of practicing nurses support the provision of hospital abortion services?); (b) questions about the relationships between variables (e.g., Is there a positive association between endorsement of hospital abortion services and support for implementing hospice care among nurses?); or in cases where a survey design is repeated over time in a longitudinal study; (c) questions about predictive relationships between variables over time (e.g., Does Time 1 endorsement of support for hospital abortion services predict greater Time 2 burnout in nurses?). An experimental design systematically manipulates one or more variables in order to evaluate how this manipulation impacts an outcome (or outcomes) of interest. Importantly, an experiment isolates the effects of this manipulation by holding all other variables constant. When one group receives a treatment and the other group does not (which is a manipulated variable of interest), the experimenter can isolate whether the treatment and not other factors influence the outcome. For example, a sample of nurses could be randomly assigned to a 3-week expressive writing program (where they write about their deepest thoughts and feelings) or a matched 3-week control writing program (writing about the facts of their daily morning routine) to eval ...

Englishsehrish shahid

intro to statisticssehrish shahid

Find an artticle or advertisment that exemplifies the use of the sta.pdf

arkurkuri

Find an artticle or advertisment that exemplifies the use of the statistics. Then,based on the article answer the follwing quetions. (a) Identtify your source.Include the date of publication. (b)What is the population? Is the population tangible or conceptual? (c)What is the method of data collection? (d)what is the sample? (e)How was the sample obtained? (f) Decide if there seems to be a better way to take the sample? (g) Identify any one variable that reported in the article? (h) Identify the type of data and level of measurement for the variable in (g). (i) Identify and describe one statistic reported in the article. Solution Robitaille Y., Laforest S., Fournier M., Gauvin L., Parisien M., Corriveau H., Trickey F., & Damestoy N. (2005, November). Moving Forward in Fall Prevention: An Intervention to Improve Balance Among Older Adults in Real-World Settings. Am J Public Health, 95(11), 2049 – 2056. The purpose of the study was to investigate the effectiveness of a group-based exercise intervention to improve balancing ability among older adults delivered in natural settings by staff in local community organizations. In this study, the quasiexperimental design was used. The participants of this study were older adults concerned about falls. In this study, community organizations were responsible for recruiting participants and delivering the intervention. Ninety eight participants were offered the interventions by 10 community organizations in a group of 5 to 15 persons and 7 organizations recruited 102 participants (similar groups of 5 to 15 persons) for control group (with home-based exercises). Participants were assessed by a physiotherapist at the beginning of the study and 3 months later. The researchers compared the demographics, health, balance, and strength of the two groups. The mean age of participants was 73.9 years, and 84% were women. More than half of study participants lived alone, and almost 40% reported having fallen in the year before baseline assessment. Comparison of intervention and control participants at baseline did not reveal statistically significant differences in demographics, health, physical activity, or vitality indicators. Intervention participants improved more than control participants on all statistic balance indicators except one (lateral reach both sides). Intervention participants also showed greater improvement in mobility and strength indicators. The findings of this study are consistent with those of previous researchers who reported that group-based exercises targeting balance can actually improve balance among older adults. However, to our knowledge, this is the first study to demonstrate that intervention effects on balance are possible when the intervention is managed by community organizations and when participants register because they are concerned about their balance or worried about falls. The strength of the study is that the ten intervention organizations represented a broad range of enviro.

Dynamic drivers of disease in Africa: Integration of participatory research

ILRI

Statistics (2).doc

Atoshe Elmi

Problem 1123456Xf122437455763715813910106 Name: Date: Topic One: Mean, Variance, and Standard Deviation Please type your answer in the cell beside the question. 5. The following is the heart rate for 10 randomly selected patients on the unit. Find the mean, variance, and standard deviation of the data using the descriptive statistics option in the data analysis toolpak. 75, 80, 62, 97, 107, 59, 76, 83, 84, 69 6. The following is a frequency distribution fo the number of times patience use the call light in a days time. X is the number of times the call light is used and f is the frequency (meaning the number of patients). Create a histogram of the data. Sheet2 Sheet3 EXERCISE 11 USING STATISTICS TO DESCRIBE A STUDY SAMPLE STATISTICAL TECHNIQUE IN REVIEW Most studies describe the subjects that comprise the study sample. This description of the sample is called the sample characteristics which may be presented in a table or the narrative of the article. The sample characteristics are often presented for each of the groups in a study (i.e. experimental and control groups). Descriptive statistics are used to generate sample characteristics, and the type of statistic used depends on the level of measurement of the demographic variables included in a study (Burns & Grove, 2007). For example, measuring gender produces nominal level data that can be described using frequencies, percentages, and mode. Measuring educational level usually produces ordinal data that can be described using frequencies, percentages, mode, median, and range. Obtaining each subject's specific age is an example of ratio data that can be described using mean, range, and standard deviation. Interval and ratio data are analyzed with the same type of statistics and are usually referred to as interval/ratio level data in this text. RESEARCH ARTICLE Source: Troy, N. W., & Dalgas-Pelish, P. (2003). The effectiveness of a self-care intervention for the management of postpartum fatigue. Applied Nursing Research, 16 (1), 38–45. Introduction Troy and Dalgas-Pelish (2003) conducted a quasi-experimental study to determine the effectiveness of a self-care intervention (Tiredness Management Guide [TMG]) on postpartum fatigue. The study subjects included 68 primiparous mothers, who were randomly assigned to either the experimental group (32 subjects) or the control group (36 subjects) using a computer program. The results of the study indicated that the TMG was effective in reducing levels of morning postpartum fatigue from the 2nd to 4th weeks postpartum. These researchers recommend that “mothers need to be informed that they will probably experience postpartum fatigue and be taught to assess and manage this phenomenon” (Troy & Dalgas-Pelish, 2003, pp. 44-5). Relevant Study Results “A total of 80 women were initially enrolled [in the study] … twelve of these women dropped out of the study resulting in a final sample of 68.” (Troy & Dalgas-Pelish, 2003, p. 39). The researchers presen.

DQ2Patrick QueisneOne of the greatest barriers that the orga

DustiBuckner14

DQ2 Patrick Queisne One of the greatest barriers that the organization I am at for my practicum has with implementation of evidence-based practice (EBP) is education. Historically, the use of would tactics such as mentorship, online learning modules, in person skills days, and lectures. However, the COVID-19 pandemic forced facilities shift in person educational avenues with an attempt to adapt by using technology. Live streaming videos rapidly became the go to replacement for the in-person class. This was the same approach that was taken by nursing programs across the country to replace clinical time for nursing students. Now there are new graduate nurses entering facilities with little, if any, in person clinical time. Staff has now realized the opportunity to have flexibility for training as there is no commute time associated with attending virtual sessions. However, as the facility seeks to return to the new normal, in person classes are not well received. The intent of continuing education is to help keep nurses informed of the latest EBP (Fletcher, 2016). Now faced with a lack of staff engagement related to long working and staffing shortages leaves the empty classrooms for in-person education. From an educational standpoint, the first part of developing a plan to determine how individuals in the organization want the information delivered. This involves having open lines of communication between educators for the facility and the staff receiving the education. References Fletcher, S. (2016). Nurse education specialist utilizing career coaching to encourage lifelong learning. Journal of Nursing Education and Practice, 6(6), 71-74. doi: 10.5430/jnep.v6n6p71 Assignment Task 2 Respond to one of your colleague’s posts in 125 words response and explain how you might see the implications differently. Colleague Response Romel Jimera Top of Form For this week's discussion on the relationship between data variability, sample size, and confidence level, I chose the "Size of the Place in 1000s" as my quantifiable variable, utilizing the General Social Survey dataset. The mean Age from that dataset is 49.01. To better appreciate the tradeoff between lowering the risk of our confidence in estimations and increasing precision, I entered a random sample size of 100 and 400 with 90 and 95 percent confidence levels, using IBM SPSS Statistics software. Table 1 In Table 1, the left table shows a random sample of 100, a mean of 324.90, and a standard error of 121.911. Using a 95% confidence interval (CI), the estimation was only 5% off (Frankfort-Nachmias et al., 2021). Meaning we are 95% confident that the actual average size of the place in 1000s is not less than 83 and not more than 566.8. However, with a 90% confidence level in the right table, all the values remain the same except for the CI (122.48, 527.32). Although the CI width is shorter than the previous one, there is more precision, but the chance of error has increased to 10%. C ...

STAT225 Introduction to Statistics in the Behavioral Sciences.docx

dessiechisomjj4

STAT225: Introduction to Statistics in the Behavioral Sciences 1. In a school election, five people run for student body president. The actual number of votes for each candidate would be a(n) variable. If the total number of votes were removed and the candidates were listed in order of least to most popular, this would be a(n) variable. a. ratio; ordinal b. ordinal; ratio c. ratio; nominal d. nominal; ordinal 2. A researcher was interested in the effects of gender on attitudes toward women in leadership positions. The researcher surveyed a group of individuals, 12 of whom were men and 12 of whom were women. In this example, what is the explanatory/independent variable? a. type of leadership position b. the 12 women in the study c. the gender of the participants d. the participants' attitudes toward women in leadership positions 3. A researcher was interested in the effects of gender on attitudes toward women in leadership positions. The researcher surveyed a group of individuals, 12 of whom were men and 12 of whom were women. In this example, what is the response/dependent variable? a. type of leadership position b. the 12 women in the study c. the gender of the participants d. the participants' attitudes toward women in leadership positions Please use the following information to answer questions 4 through 9 An industrial psychologist at a company has heard that desk bikes could help employees to lose weight, increase their stamina, and improve productivity. Sixteen employees were provided with desk bikes and the total number of pounds they lost, after one month, was recorded. Here are the data, in pounds lost, per employee: 4 8 12 0 2 20 18 0 12 6 12 16 10 8 12 4 4. What is the range of this distribution? a. 0 t o 20 b. 20 c. 18 d. 4 5. What is the mean number of pounds that were lost by the employees in one month? a. 9.88 b. 10.4 c. 12 d. 9 6. What is the median number of pounds that were lost by the employees in one month? a. 8 b. 9 c. 10 d. 11 7. What is the variance of the number of pounds that were lost by the employees in one month? a. 37.33 b. 9.72 c. 9.85 d. 6.11 8. What is the Interquartile range for this distribution? a. 4 b. 8 c. 9 d. 12 9. How many outliers are in this distribution? a. 0 b. 1 c. 2 d. Unable to determine from this information The following graph depicts the typical relationship found between physiological arousal (anxiety) levels (e.g., range from 0 = no anxiety to 10=extreme anxiety) and test performance (e.g., percentage of correct answers on test). Please use the following information to answer questions 10 and 11. 100% Test Performance (in Percentage) 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Relationship Between Physiological Arousal Level and Test Performance 0 2 4 6 8 10 Physiological Arousal Level 10. Based on this graph, what type of relation exists between physiological arousal level and test performanc.

Please this work is due today and you have to make use of the learni.docx

blazelaj2

Please this work is due today and you have to make use of the learning resource below the assignment Discussion: Central Tendency and Variability Understanding descriptive statistics and their variability is a fundamental aspect of statistical analysis. On their own, descriptive statistics tell us how frequently an observation occurs, what is considered “average”, and how far data in our sample deviate from being “average.” With descriptive statistics, we are able to provide a summary of characteristics from both large and small datasets. In addition to the valuable information they provide on their own, measures of central tendency and variability become important components in many of the statistical tests that we will cover. Therefore, we can think about central tendency and variability as the cornerstone to the quantitative structure we are building. For this Discussion, you will examine central tendency and variability based on two separate variables. You will also explore the implications for positive social change based on the results of the data. To prepare for this Discussion: Review this week’s Learning Resources and the Central Tendency and Variability media program. Review the Chapter 4 of the Wagner text and the examples in the SPSS software related to central tendency and variability. From the General Social Survey dataset found in this week’s Learning Resources, use the SPSS software and choose one quantitative variable and one categorical variable Note: this dataset will be different from your Assignment dataset). As you review, consider the implications for positive social change based on the results of your data. By Day 3 Post, present, and report a descriptive analysis for your variables, specifically noting the following: For your quantitative variable: Report the mean, median, and mode. Report the standard deviation. What would you say would be the better measure for central tendency? (i.e., mean, median, or mode) and why? How variable are the data? How would you describe this data? What are the possible implications for positive social change based on the results of your data? Post the following information for your categorical variable: A frequency distribution. An appropriate measure of variation. How variable are the data? How would you describe this data? What are the possible implications for positive social change based on the results of your data? Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style. Learning Resources Required Readings Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications. Chapter 4, “Measures of Central Tendency” (pp. 96–134) Chapter 5, “Measures of Variability” (pp. 135–176) Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Pub.

Intoduction to statistics

SachinKumar1799

Samples Types and Methods

Tarek Tawfik Amin

Community and Public Health (Week 2&3)

Ana Anastacio

MGT 4399 Quality Management Module 5 Journal Root C

MoseStaton39

MGT 4399: Quality Management Module 5 Journal: Root Cause Analysis Guidelines and Rubric In this journal, you will continue to build your understanding of the DMAIC methodology of quality management by applying the skills and knowledge you have learned in this module to the process you have been exploring throughout the previous modules’ journals. Specifically, you will apply a Lean root cause analysis tool such as the 5 Whys, fishbone diagram, Pareto chart, Failure Mode and Effects Analysis (FMEA), scatter plot diagram, etc. For this journal assignment, be sure to include the following: ● Identify the process problem ● Apply a Lean root cause analysis tool to reduce the problem to its logical root cause solution ● Determine the root causes Guidelines for Submission: Your journal entry should include either an attachment or link to a diagram, bulleted list, flowchart, or bar graph of the problem and solution depending on the tool selected. Instructor Feedback: This activity uses an integrated rubric in Blackboard. Students can view instructor feedback in the Grade Center. Rubric Criteria Exemplary (100%) Needs Improvement (75%) Not Evident (0%) Value Process Problem Identifies the process problem. N/A Does not identify the process problem. 10 Lean Root Tool Applies a Lean root cause analysis tool. Application of a Lean root cause analysis tool is unclear or inappropriate. Does not apply a Lean root cause analysis tool. 40 Root Cause Determine the root causes. Root causes are unclear or inaccurate. Does not determine the root causes. 40 Mechanics No grammar or spelling errors that distract the reader from the content. All sources used are cited using APA Style, 6th ed. Minor errors in grammar or spelling that distract the reader from the content. All sources used are cited using APA Style, 6th ed. Major errors in grammar or spelling that distract the reader from the content and/or errors made in citing sources using APA Style, 6th ed. 10 MGT 4399: Quality Management Total = 100% Topic: Disparities in healthcare in USA Writing chapter 4 (Data and Analysis) Everything that needs to be in this chapter is on the PowerPoint. Again, only chapter 4 needed. 8 pages Reporting Results This chapter includes a presentation and analysis of the data. The tone of the chapter is purely objective, devoid of assumptions and interpretations. Following a summary of the research data (include whether your data are qualitative or quantitative), Chapter IV should be organized in a manner consistent with the research hypotheses. First, present data related to the first hypothesis. (3 hypotheses for this topic) It is usually a good idea to restate your hypothesis. (See initial proposal document) If you use tables, which are an effective way to present quantitative data, your description and analysis of the data should precede the table, not come afterwards. Be sure to sta ...

Lesson 3 basic terms in statistics

Maris Ganace

Levels of Measurement.pdf

AlemAyahu

Reducing Anomia

Ashley Lott

Intro to statistics formatted (1)Ulster BOCES

Intro to statistics formattedUlster BOCES

A Model For Presenting Threats To Legitimation At The Planning And Interpreta...

Sarah Adams

Stratification of clinical survey data

IJDKP

Data stratification is the process of partitioning the data into distinct and non-overlapping groups since the study population consists of subpopulations that are of particular interest. In clinical data, once the data is stratified into sub populations based on a significant stratifying factor, different risk factors can be determined from each subpopulation. In this paper, the Fisher’s Exact Test is used to determine the significant stratifying factors. The experiments are conducted on a simulated study and the Medical, Epidemiological and Social Aspects of Aging (MESA) data constructed for prediction of urinary incontinence. Results show that, smoking is the most significant stratifying factor of MESA data, showing that the smokers and non-smokers indicates different risk factors towards urinary incontinence and should be treated differently.

Reply to 2 peers and provide them each with a potential or actual .docx

sodhi3

Reply to 2 peers and provide them each with a potential or actual study using a mixed method design to address their practice challenge. Be sure to provide citations. For week 2, you will add the following content to your formal literature synthesis based on the practice challenge you described last week. 1. Define problem statement, hypothesis, and PICOT statement. Cite resources A problem statement is developed by the researcher and identifies a potential problem that is relevant to practice. A hypothesis is a fundamental explanation based on limited data and observation that serves as a foundational starting point with which to proceed with further investigation. PICOT stands for Population (P), Intervention (I), Comparison (C), Outcome (O) and Time-frame (T) of intervention. A PICOT statement is a reliable "formula" for producing answerable, researchable questions (Polit & Beck, 2017). 2. Develop a problem statement, potential hypothesis, and potential PICOT statement based on your practice challenge. Nursing staff shortages impact patient care as well as the nurses who provide the patient care. Nurse staffing needs vary depending on acuity, day or night shift, procedures, and any number of unforeseen events. Short staffing jeopardizes not only the patients but the license and health of the nurses as well. A potential hypothesis regarding this topic may be that if nursing staffing was improved, the occurrence error related patient incidences. The population affected in this PICOT statement is the patients. The intervention in this PICOT statement is that the nursing staffing levels can be increased to alleviate the shortages. The comparison will be a hospital that remains at lower staffing levels. The outcome will be the number of nurse retention compared in both hospitals. The comparison time will be one year. 3. Identify potential (ones you make up) or actual studies using 2 different methodologies (qualitative and quantitative). Be sure to provide citations. A qualitative study that evaluates the patient effects of nurse short staffing is study performed by Clark, P. A., Leddy, K., Drain, M., & Kaldenberg, D. “state nursing shortages and patient satisfaction: more RNs—better patient experiences” (2007). In this study, the do a qualitative analysis on the quality of patients care and the correlation between adequate nursing staffing. A quantitative study that evaluates the patient effects of nurse short staffing is “nurse staffing and patient outcomes: a longitudinal study on trend and seasonality by He, J., Staggs, V. S., Bergquist-Beringer, S., & Dunton, N. (2016). In this study He performed a longitudinal study based off quarterly unit-level nursing data in 2004–2012 were extracted from the National Database of Nursing Quality Indicators (NDNQI). Second Post The opioid misuse and abuse has become an epidemic nationwide. There has been a 30 percent increase in overdoses in the U.S. from July 2016 through September 2017. ...

29510Nominal Data and the Chi-Square TestsJupiterimag.docx

rhetttrevannion

295 10Nominal Data and the Chi-Square Tests Jupiterimages/Stockbyte/Thinkstock Chapter Learning Objectives After reading this chapter, you should be able to do the following: 1. Describe nominal data. 2. Complete and explain the chi-square goodness-of-fit-test. 3. Complete and explain the chi-square test of independence. tan82773_10_ch10_295-320.indd 295 3/3/16 2:33 PM © 2016 Bridgepoint Education, Inc. All rights reserved. Not for resale or redistribution. Section 10.1 Nominal Data Introduction When an important development in statistical analysis took place in the early part of the 20th century, more often than not Karl Pearson was associated with it. As the text previously noted, many of those who made important contributions were members of the department that Pear- son founded at University College London. Those who gravitated to Pearson’s department included William Sealy Gosset, who developed the t tests; R. A. Fisher, who developed analysis of variance; and Charles Spearman, who did the early work on factor analysis. Although social relations among these men were not always harmonious, they were enormously productive scholars, and this was particularly true of Pearson. Besides the correlation coefficient named for him, Pearson developed an analytical approach related to Spearman’s factor analysis called principal components analysis, as well as the procedures that are the subjects of this chapter, the chi-square tests. (The Greek letter chi [χ] is pronounced “kye” and rhymes with sky. Chi is the Greek equivalent of the letter c, rather than the letter x, which it resembles.) 10.1 Nominal Data With the exception of Spearman’s rho in Chapter 8, Chapters 1 through 9 have focused on procedures designed for interval or ratio data. Sometimes, however, the data are neither interval scale nor the ordinal-scale data that Spearman’s rho accommodates. When the data are nominal scale, researchers often use one of the chi-square tests. Because our focus has been so much on interval- and ratio-scale data, it might be helpful to review what makes data nominal scale. Nominal data either fit a category or do not, which is why they are sometimes referred to as “categorical data.” Because of this presence-or- absence quality, analyses of nominal data are based on counting how frequently they occur, and for that reason they are also called “count data.” Compared to ratio, interval, and even ordinal data, nominal data provide relatively little information. They reveal only the presence or absence of a characteristic, not how much of the characteristic, or how the individual’s pos- session of the characteristic compares to others in the category. To illustrate: when people are classified according to whether they are 1. left-handed or right-handed, or 2. Buddhist, Jewish, Muslim, or 3. African American, Hispanic, or Native American, or 4. blue-eyed or brown-eyed, or 5. introverted or extroverted, then the resulting.

Discussion Central Tendency and VariabilityUnderstanding descript.docx

mickietanger

Discussion: Central Tendency and Variability Understanding descriptive statistics and their variability is a fundamental aspect of statistical analysis. On their own, descriptive statistics tell us how frequently an observation occurs, what is considered “average”, and how far data in our sample deviate from being “average.” With descriptive statistics, we are able to provide a summary of characteristics from both large and small datasets. In addition to the valuable information they provide on their own, measures of central tendency and variability become important components in many of the statistical tests that we will cover. Therefore, we can think about central tendency and variability as the cornerstone to the quantitative structure we are building. For this Discussion, you will examine central tendency and variability based on two separate variables. You will also explore the implications for positive social change based on the results of the data. To prepare for this Discussion: Review this week’s Learning Resources and the Central Tendency and Variability media program. Review the Chapter 4 of the Wagner text and the examples in the SPSS software related to central tendency and variability. From the General Social Survey dataset found in this week’s Learning Resources, use the SPSS software and choose one quantitative variable and one categorical variable Note: this dataset will be different from your Assignment dataset). As you review, consider the implications for positive social change based on the results of your data. By Day 3 Post, present, and report a descriptive analysis for your variables, specifically noting the following: For your quantitative variable: Report the mean, median, and mode. Report the standard deviation. What would you say would be the better measure for central tendency? (i.e., mean, median, or mode) and why? How variable are the data? How would you describe this data? What are the possible implications for positive social change based on the results of your data? Post the following information for your categorical variable: A frequency distribution. An appropriate measure of variation. How variable are the data? How would you describe this data? What are the possible implications for positive social change based on the results of your data? Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style. Learning Resources Required Readings Frankfort-Nachmias, C., & Leon-Guerrero, A. (2015). Social statistics for a diverse society (7th ed.). Thousand Oaks, CA: Sage Publications. Chapter 4, “Measures of Central Tendency” (pp. 96–134) Chapter 5, “Measures of Variability” (pp. 135–176) Wagner, W. E. (2016). Using IBM® SPSS® statistics for research methods and social science statistics (6th ed.). Thousand Oaks, CA: Sage Publications. Chapter 4, “Organization and Presentation of Information” Chapter 11, “Editing Output” Datas.

Descriptive StatisticsNameQNT561DateInstructor’s Name.docx

theodorelove43763

Descriptive StatisticsNameQNT/561 Date Instructor’s Name SHORT TITLE OF PAPER 1 Running head: DESCRIPTIVE STATISTICS 1 Descriptive Statistics Determine the appropriate descriptive statistics. Note: If the data was normally distributed, use the mean and standard deviation. If the data was skewed significantly, use the median and interquartile range. Numeric Variable Name1 Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Numeric Variable Name2 (if applicable) Distribution: State if not normally distributed Central Tendency: Dispersion: Number: Min/Max: Confidence Interval: (if distribution is normal) Attribute Variable Name (if applicable) Create a bar chart. Describe the proportions. Descriptive Statistics Interpretation Numeric Variable Name1 Describe the variable in laymen terms. Numeric Variable Name2 (if applicable) Describe the variable in laymen terms. DESCRIPTIVE STATISTICS 2 Appendix A Raw data used in the analysis Fit data to one page. Appendix B Charts and Tables This part of the paper will include items that are then cited in the body of the paper. Usually, large items are placed here not to distract from reading the paper. Appendix C Descriptive Statistics This part of the paper will include descriptive statistics. Create a Microsoft® Excel® spreadsheet with the two variables from your learning team's dataset. Analyze the data with MegaStat®, StatCrunch®, Microsoft® Excel®or other statistical tool(s), including: (a) Descriptive stats for each numeric variable (b) Histogram for each numeric variable (c) Bar chart for each attribute (non numeric) variable (d) Scatter plot if the data contains two numeric variables Determine the appropriate descriptive statistics. (a) For normally distributed data use the mean and standard deviation. (b) For significantly skewed data use the median and interquartile range. Use the Individual Methodology Findings Template to complete the descriptive statistics. Use the Descriptive Statistics and Interpretation Example to develop an interpretation of the descriptive statistics. Format your paper consistent with APA guidelines. Submit both the spreadsheet and the completed Individual Methodology Findings Template. Click the Assignment Files tab to submit your assignment. Please use the variables from this except: The size of this population is 20 suppliers. These suppliers exclusively produce and make available for sale the material that is needed for manufacturing. In order to develop the sampling design it is important to identify the independent and dependent variables. Independent variables are variables that are manipulated or treated in a study in order to see what effect differences in them will have on those variables proposed as being dependent on them (Riyami, 2008). The independent variable in this research is the cost of the raw material. Dependent variables are variables .

FROM THE CLASSROOM TO AN OPINION NOTE: COMPLEMENTARY ANALYSIS OF THE GENETIC ...

International Educational Applied Scientific Research Journal (IEASRJ)

Here, we describe a learning strategy that results an excellent choice for a first approach of students to produce scientific knowledge that can be confronted in the scientific field as well as recognize in this knowledge the transferability to the natural resources management. Nowadays, the availability of several Population Genetics software together with public molecular database represents a valuable tool of great assistance for teachers of this discipline. In this way, we implemented a lecture where the students worked with empirical data set from a recent published article. The students joined theoretical concepts learned, computational software free available and empirical data set. The development of the activity comprised four steps: i) estimate population genetics parameters using software recommended by teachers, ii) understand results in a biological sense, iii) read the original manuscript from dataset authors and iv) compare both results in a comprehensive way. The students assumed the challenge under a reflective look and they kept a very fruitful discussion playing a role of population geneticists. Their exchange of ideas allowed them arrive to the conclusion that Manilkara zapota populations keep high levels of genetic diversity, although Ancient Maya left traces in the genetic makeup of these non-native populations with different management histories.

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