Study Guide for Exam 1

Study Guide for Exam 1 (Module 2, Chapters 7-8)

Single, Dependent, and Independent t-tests

The following topics are covered on the exam in Module 2. Questions are drawn randomly from a test bank, so you should be prepared for getting questions on any of the following topics. The list below includes page numbers to help you identify where in the chapter each topic can be located.

Elements of formula for estimating population variance from sample (p. 226)

What are degrees of freedom? How are they calculated? (p. 226-7)

Understand biased estimate (p. 225-6)

Know how to compute estimated population variance (formula 7-1)

What is the modality of the t distribution (unimodal, bimodal, multimodal?) (p. 228)

Know: Formula for effect size is (M1 – M2)/s; in words: (mean 1 – mean 2)/ standard deviation AND be familiar with cut-offs for Cohen’s d (p. 247)

Formula for t score for single sample test is (M – u)/sm; in words (sample mean- population mean)/standard deviation of distribution of means (p. 230) Notice the difference between the effect size and t score formulas—effect size uses standard deviation, t score uses sd of distribution of means, which is different.

Know how to find cut-off t score using sample size, significance level, and t table.

Know when using a t-test for dependent means is appropriate

Which t-test uses difference scores?

Formula for t score for dependent samples test: p. 238, table 7-6

Be familiar with assumptions of dependent means t-test (p. 247)

Know how to interpret whether or not a result is significant based on the p value

Who invented the t-test? Be familiar with experiment that led to it. (box p. 224)

Know in what situation to use an independent t-test and what kind of distribution the comparison distribution is. (p. 271)

Understand what a basic research (alternative) hypothesis looks like for an independent t-test in terms of sample/population terminology (p. 278-80)

Define pooled estimate of population variance (p....