Non-Parametric Statistics
This week, you have expanded on your knowledge of non-parametric statistics. In this Application, you will perform two non-parametric statistical tests.
To prepare for this Application:
• Review Chapter 6 of the Field text for a description of non-parametric statistics, and examples of conducting non-parametric tests using IBM SPSS Statistics.
• Review Chapter 5 from the APA manual, "Displaying Results."
• Review the media resources demonstrating the linear multiple regression.
The assignment:
Complete Smart Alex’s Task #1 on p. 259 to analyze the file MenLikeDogs.sav data set with a Mann-Whiney test. Then complete Smart Alex’s Task #3 on p. 260 to analyze the file Eastenders.sav data set with a Friedman’s ANOVA.
Report your findings in APA format according to the guidelines in the IBM SPSS Statistics Application Assignment Guidelines handout. The final document should be 3-4 pages long.
Week 7: Non-Parametric Statistics
Introduction
In RSCH-7200/7201/8200/8201, you had a brief introduction to non-parametric statistics, but the application dealt only with categorical analyses (i.e. the Ch-square test of independence). The focus this week is on hypothesis testing. The t test and ANOVA are examples of parametric hypothesis tests, and although those tests are very helpful, sometimes the underlying assumptions for those tests are not met. What can you do in these situations? The answer lies in non-parametric tests.
Non-parametric tests do not require the assumptions that are necessary for parametric tests, and although non-parametric tests have slightly less power, they are appropriate in situations where a parametric test is not applicable. This often occurs with small samples, so knowing about these tests can be very useful in research in the social sciences.
This week, you will learn how to work with and utilize non-parametric statistics.
Learning Outcomes
By the end of this week, you will be able to (for non-parametric statistics):
• State underlying assumptions
• Determine when appropriate
• State null and alternative hypotheses
• Analyze data using IBM SPSS Statistics
• Interpret and report the results with IBM SPSS Statistics, including effect size
• Describe sample size
• Report results in APA format
• Construct a theoretical framework to support the research proposal.
•
• Required Resources Course Text: Discovering Statistics Using SPSS Statistics
Chapter 6, "Non-parametric models"
In this chapter you will learn about non-parametric statistics, when it is appropriate to use a non-parametric procedure, and how to interpret results using IBM SPSS Statistics.
• Course Text: Research Methods in the Social Sciences
o Chapter 2, "Conceptual Foundations of Research"
This text will assist you in developing and articulating a theoretical framework for your final research proposal.
• Handout: Statistics Application Evaluation Criteria (Word document)
This handout will guide you in completing and submitting your linear multiple regression Application 1 Assignment for this week.
• Software: IBM SPSS Statistics Standard GradPack (current version). Available in Windows and Macintosh versions. Please refer to the IBM SPSS Software area on the left navigation bar for more information on how to install, register, and license this software.
You will use this software to complete this week’s Application 1 Assignment.
• Website: StatSoft. (2010). Nonparametric statistics. Retrieved from https://www.statsoft.com/textbook/nonparametric-statistics/
This website provides an overview of nonparametric statistics procedures, including the purpose of each and when each would best be used.
• Website: Plonsky, M. (2009). Nonparametric statistics. Retrieved from https://www.uwsp.edu/psych/stat/14/nonparm.htm
this website provides an introduction to nonparametric statistics, including chi square.
Research Toolkit
Research Design
• Website: Web Center for Social Research Methods
https://www.socialresearchmethods.net
This website is for people involved in applied social research and evaluation. You will find several resources and links to other locations on the web that deal in applied social research methods.
• Website: Cengage Research Methods Workshops
https://www.wadsworth.com/psychology_d/templates/student_resources/workshops/resch_wrk.html
This website offers many useful workshop topics such as experimental methods, reliability and validity, surveys, sampling methods, ethical issues, and evaluating published research.
Statistics and SPSS
• Website: SPSS Student Resource Center
www.ibm.com/software/analytics/spss/support/techsupport.html
The SPSS student support site provides a knowledgebase and allows students to request assistance from SPSS Technical Support staff. Since this site is produced and maintained by the creators of the PASW software, it is the best place to go when you have a question about the software.
• Website: UCLA’s ‘What Statistical Analysis Should I Use?’ Table
https://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
This statistics table shows general guidelines for choosing a statistical analysis, and links showing how to do such tests using SAS, Stata and PASW. This is a good place to go if you are not sure which statistical test would best answer the research question you have.
• Website: Statistics Hell
https://www.statisticshell.com/html/apf.html
This site is Andy Field’s (the author of the main course text) online statistics resource. This site provides additional explanations beyond the textbook and more examples. This is the best place to go when you are confused about how to do a particular test.
• Website: Cengage Statistics Workshops
https://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stats_wrk.html
This website offers many useful workshop topics such as experimental methods, reliability and validity, surveys, sampling methods, ethical issues, and evaluating published research.
Optional Resources
• Text: Conover, W. J. (1999). Practical Nonparametric Statistics (3rd ed.). New York, NY: John Wiley & Sons.
• Text: Publication Manual of the American Psychological Association
o Chapter 5, "Displaying Results"
• Media: Data Cleaning and Dealing with Assumptions (Adobe Captivate)
Dr. Jennifer Morrow explains the assumptions surrounding many of the tests you will study and explains ways that you can manage data that violates these assumptions. This Flash-based demonstration will open in a new window.
Click here to download a transcript of this demonstration.
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