What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp’s friendly and approachable guide to real-world statistics answers these questions. Intermediate Statistics Using SPSS is not about abstract statistical theory or the derivation or memorization of statistical formulas–it is about applied statistics. With jargon-free language and clear processing instructions, this text covers the most common statistical functions–from basic to more advanced. Practical exercises at the conclusion of each chapter offer students an opportunity to process viable data sets, write cohesive abstracts in APA style, and build a thorough comprehension of the statistical process. Students will learn by doing with this truly practical approach to statistics. Free downloadable tutorial videos provide an overview of each statistical method!

# t Test and Mann-Whitney U Test

### t Test and Mann-Whitney U Test

The difference between a violin and a viola is that a viola burns longer.

—Victor Borge

### Learning Objectives

Upon completing this chapter, you will be able to do the following:

• Determine when it is appropriate to run a t test.
• Verify that the data meet the criteria for t test processing: normality, n, and homogeneity of variance.
• Order a t test.
• Interpret the test results.
• Comprehend the α and p value.
• Resolve the hypotheses.
• Know when and how to run and interpret the Mann-Whitney U test.
• Write an appropriate abstract.
• Understand the implications of Type I and Type II errors.
• Apply techniques for reducing the likelihood of committing Type I and Type II errors.

NOTE: From here forward, the M character will be used to symbolize the mean.