GW08 Hypothesis testing & power:  study guide
NOTE 1: include each question with its corresponding answer!
NOTE 2:  paraphrase explanations from the text - don't merely copy verbatim.

1  Define: Hypothesis testing.
2  Identify, define, and note an example of the two hypotheses used in hypothesis testing.
3  Explain how the distribution of sample means is divided when evaluating hypotheses.
       Include a sketch that depicts the division.
4  Define and explain alpha level and critical region.
       Include a sketch that depicts the critical region.
5  What are the two possible decisions regarding the viability of the null hypothesis?
6  Explain why we test the null hypothesis rather than the alternative hypothesis.
7  Explain the z-score formula in words regarding the actual difference between the sample mean & the
        pop mean versus the expected difference between them.  Then explain what we mean by a "test
        statistic," and the z-score's use as a general model (a ratio) for most test statistics (GW 235 - 236).
        [Note:  don't simply copy the text's wording, since copying is NOT the same as explaining. 
         Paraphrasing is, of course, certainly O.K.]
8  We are now entering fully into the "inferential statistics" section of the course.  Explain why we call it  
        "inferential."
9   Identify, explain, and provide an example of each of the two types of errors that are possible in
        hypothesis testing. [Be able to sketch, label, and explain the "possible outcomes" decision matrix
        illustrated on page 239 of GW.]
10  Explain how alpha level is related to decision errors in hypothesis testing.
11  Explain the relations between different values of alpha and rejecting Ho (i.e., demonstrating a treatment
        effect or group differences).  Include a sketch.
12 Explain statistical significance.
13 Identify and explain the three factors than influence a hypothesis test.
14 Name and explain the four assumptions that must be made in order to use z-scores in hypothesis testing.
15 Explain and compare & contrast one-tailed and two-tailed hypothesis tests; note when each is used, and
      provide a real-world example of each [make up an example that is not in the text].
16 One of the concerns that scientists often express regarding hypothesis testing is based on "treatment
      effect" issues.  Explain those issues & note how they can be addressed in a research report via "effect
      size."
17  In correlation and regression we usually report r² as our measure of effect size.  Note which measure of
        effect size we use for z-tests and briefly explain how it works.
18  Define power.
20  List and explain the four factors affecting power.