What are the most common reasons you would select a non-parametric test over the parametric

Question #7

• Please review the professor’s notes from the last assignment – thank you.
• Though this is one question, it has two parts. Each part must be its own separate MS Word document by cutting and pasting the SPSS output into the document after each question. Please read the instructions below to ensure you are pasting the correct material into your document.
• All responses have a minimum word requirement of 250 words per question for part A.
• Please save Part A and Part B as two separate MS Word documents.
• The SPSS data files that coordinate with each part of the questions are attached.
• I have attached the answer sheet already formatted for answers/responses.
• SPSSS Data sets have also been attached.

Complete the following:

Part A

Using an MS Word document, provide short answers to the following questions. Length: 250 words or less for each question.

Complete the following:

1. What are the most common reasons you would select a non-parametric test over the parametric alternative?
2. Discuss the issue of statistical power in non-parametric tests (as compared to their parametric counterparts). Which type tends to be more powerful? Why?
3. For each of the following parametric tests, identify the appropriate non-parametric counterpart:
   1. Dependent t test
   2. Independent samples t test
   3. Repeated measures ANOVA (one-variable)
   4. One-way ANOVA (independent)
   5. Pearson Correlation

Part B

In this assignment, you will perform the non-parametric version of the tests you used previously. In each case, assume that you opted to use the non-parametric equivalent rather than the parametric test.

Using the data files from earlier assignments, complete the following tests and paste your results into your document:

1. Activity 4a: non-parametric version of the dependent t test
2. Activity 4areformatted: non-parametric version of the independent t test
3. Activity 4C: non-parametric version of the single factor ANOVA