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Non-Parametric Models

Non-Parametric Models

For this assignment, you will complete the five steps below for Task 5 in your Field textbook, page 248, using the Oxoby (2008) Offers.sav file. Put yourself in the position of being a researcher tasked with figuring out whether the number of offers was significantly different for people listening to Bon Scott versus Brian Johnson, and complete the following five steps. 
Step A: Questions and Hypotheses 
Begin your project by developing a solid foundation to guide the study. 

Develop a  quantitative research question appropriate for the Mann-Whitney test. 
State the null and alternative hypotheses appropriate for a Mann-Whitney test.
Identify the level of measurement for each variable (such as nominal, ordinal, interval, or ratio).
Using the decision tree in the back of your Field textbook, describe the selection process for the Mann-Whitney test used in this assignment.  
Identify the significance level (alpha) for the test. 

Step B: Test the Assumptions 
While non-parametric tests are sometimes called assumption-free tests (Field, 2018, p. 213), we still test for normality and homogeneity of variance. In fact, the results of these tests and our inability to fix the issues are why we end up conducting non-parametric tests.  

Identify and address any missing data, oddly coded data, and outliers. 
Identify and test the assumptions (for example, normality and homogeneity of variance) using SPSS. 
Create the appropriate graphs for visual analysis of the assumptions. 
Analyze the results of the tests, address any issues, and state your conclusions for each assumption. 

Note: Review the Field textbook, Chapter 6, “The Beast of Bias” and videos for more on how to complete this step. 
Step C: Run the Test and Results

Explore the data and relationships by creating the appropriate graphs for visual analysis. 
Test the null hypothesis using a Mann-Whitney test and report the results.
Analyze and interpret the results and make a decision whether to reject the hypothesis. 
Justify your decision and describe what it means.  

Note: Review the Field textbook, Chapter 7,Non-Parametric Model” and the companion website videos for more on how to complete this step.
Step D: Limitations and Conclusions

Compute and analyze the statistical power using G*Power. 
Identify and describe the implications of the limitations from Steps A, B, and C.   
Interpret the results and draw conclusions. Describe what the results of the test mean, considering the limitations.  

Note: Review using G*Power to compute the statistical power. 
Step E: Report 

Create an APA-formatted report detailing Steps A, B, C, and D, in that order. 
Use sections headings that match the labels on Steps A through D. Use subsection headings for each major sub-step or test. Make sure you include a cover page with the appropriate information, including your name. 
Support your discussion with credible research methods references (such as Field, 2018) and include an APA-formatted reference list of all sources cited in the report. 
Refer to the assignment scoring guide to review how this assignment will be graded.
Save your report as YourLastName_U6.doc and submit it along with YourLastName_U6.spv to the Unit 6 Assignment. 

Reference
Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Thousand Oaks, CA: Sage.

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