Guide to using the learning objectives

# Pages 455-481

1.                Define1 factorial experiment. Contrast4 factorial experiments with the multiple-group experiments discussed in Chapter 11.

2.                Produce5 a 2 x 2 factorial experiment studying the effects of chocolate consumption and listening to music on test performance.

3.                Compare4 and contrast4 your 2 X 2 factorial experiment with

a.     An experiment that examines four levels of a single independent variable (e.g., four levels of chocolate consumption).

b.    Four simple experiments.

4.                Explain2how your 2 x 2 factorial experiment could yield each of the following:

a.     four simple main effects;

b.    two overall main effects (in your explanation,  (a) define1main effect  and (b) explain2 how overall main effects can be estimated from simple main effects); and

c.     an interaction (in your explanation, (a) define1 interaction and (b) explain how the interaction can be estimated from simple main effects).

5.                Describe,1in your own words, what an interaction is. Produce5 an example of an interaction. Describe2 the relationship between interactions and moderating variables. Describe2 the relationship between interactions and external validity. Explain2 why psychologists are interested in interactions.

6.                Using the discussion in this chapter as an example, outline3 the questions you could answer with the 2 x 2 factorial experiment you generated to study the effects of chocolate consumption and listening to music on test performance.

# Pages 481-504

7.                Distinguish4between a main effect and an interaction. Explain2 how you could have an interaction without a main effect.

8.                Produce5a list of the eight different patterns of results you could get from a 2 x 2factorial experiment. Using your 2 x 2 experiment on chocolate consumption, listening to music, and test performance as your example, illustrate3 (using either graphs or tables of hypothetical data) how your results could lead to each of these eight potential patterns.

9.                Suppose that you conduct your experiment on chocolate consumption, listening to music, and test performance.  Distinguish4between the conclusions you would draw if you obtained a main effect for chocolate consumption but no interaction versus if you obtained a main effect for chocolate consumption and an interaction.

10.           Suppose you expand your experiment to include three levels of chocolate consumption. You have 36 participants. Compute3 the missing values for the table below.

 Source of Variance Sum of Squares df MS F Chocolate consumption main effect 8 Listening to music main effect 6 Interaction between chocolate consumption and listening to music 20 Error Term 60 Total

11.           Distinguish4between ordinal and disordinal interactions. Explain2 why ordinal interactions may be the result of having ordinal data.

# Pages 504-508

12.           Imagine that a simple (two-group) experiment finds that students taking a psychology test printed on blue paper do better than students taking the same test printed on white paper. Expand on this simple experiment by generating5 a 2X 2 factorial experiment that includes a replication factor. Justify6why your 2 X 2 experiment has more external validity than the simple experiment had.

13.           Devise5a factorial experiment by adding a potential moderating variable to a simple experiment (you may use the simple experiment referred to in the previous objective). Describe2, using the terms main effects and interaction, a pattern of results that would support the idea that you found a moderating variable.  Explain2 the value of finding a moderator factor.

14.           Explain2how an interaction may indicate the effect of similarity.

# Pages 508-513

15.           Describe2the main limitation of using a nonexperimental variable in a study.

16.           Propose5and justify6 expanding the simple experiment discussed in Objective13 into a 2 X 2 factorial design by

a.     Adding a nonexperimental variable to increase the generalizability of the findings

b.    Adding a nonexperimental variable to increase the power of the design