Statistical Practice: Student T-Test To best prepare for the upcoming assignments, you must understand how to perform and interpret paired several different t-tests. SPSS makes it relatively easy to...

Statistical Practice: Student T-Test

To best prepare for the upcoming assignments, you must understand how to perform and interpret paired several different t-tests. SPSS makes it relatively easy to perform parametric testing.

To add to your statistical programming skills and prepare you for the next unit, we will be using SPSS to solve the parametric t-testing in this unit.

Instructions

For this discussion, use the data found in the Emotional Well-Being data set you created previously. You will have to use two t-tests: independent samples (unpaired) t-test and the dependent samples (paired) t-test.

Independent Samples (Unpaired) T-test

To determine the varying effects of the dietary treatment on males versus females (which are, admittedly, "independent"of each other), perform an independent samples t-test on the Well-Being dependent variable in male participants compared to the same scores in female participants. Note you will need to create a new dependent variable related to the treatment-related change in well-being scores (Hint:Change score = Post-Tx Well-Being - Baseline SF-36 Well-Being Score).

Dependent Samples (Paired) T-test

Next, to compare the effects of the Dietary Treatment on the well-being of males at baseline to well-being scores in the same males after treatment, perform a dependent (paired) samples t-test for the dependent variable Well-Being (Hint: use Baseline versus Post-Tx).

For your initial post, complete the following:

1. Describe, in your own words, 2 or 3 research project scenarios in which to use these t-tests.


2. Report,using the Emotional Well-Being data set, the results of the t-testing that you perform. Report the appropriate all the statistical outcomes, including the 95% confidence interval.


3. Provide a 1-2 sentence practical interpretation that includes a practical explanation of the different confidence intervals, based on the results.

Remember to follow the guidelines in the FEM as you prepare your post.

Response Guidelines

Read and respond to the posts of your peers according to the guidelines in the FEM.

Addressthe following in your response:

• How do the interpretations ofyour peers compare to yours?

Learning Components

This activity will help you achieve the following learning components:

• Identify normal and non-normal data distribution.


• Identify ordinal data.


• Identify the differences among t-testing, Mann-Whitney, and Wilcoxon Rank Sum testing.


• Perform the appropriate tests with data for each question.


• Identify the statistical output (estimate, p-value, confidence interval, effect size) from each statistical test.


• Select the most appropriate testing strategy for a set of data.


• Appropriately interpret the statistical output (estimate, p-value, confidence interval, effect size) resulting from each statistical test.


• Describe the practical significance of statistical test results.