Guide to using the learning objectives
1.
Define1
factorial experiment. Contrast4 factorial experiments with the
multiple-group experiments discussed in Chapter 10.
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.
Explain2
how 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) define1
main 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.
Describe1,
in 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.
7.
Distinguish4
between a main effect and an interaction. Explain2 how you could
have an interaction without a main effect.
8.
Produce5
a list of the eight different patterns of results you could get from a 2 x 2
factorial 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. Distinguish4
between 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.
Distinguish4
between ordinal and disordinal interactions. Explain2 why ordinal
interactions may be the result of having ordinal data.
12.
Define1
ceiling effect. Define1 floor effect. Explain2 how ceiling
and floor effects may create ordinal interactions.
13.
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 2
X 2 factorial experiment that includes a replication factor. Justify6
why your 2 X 2 experiment has more external validity than the simple experiment
had.
14.
Devise5
a 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.
15.
Explain2
how an interaction may indicate the effect of similarity.
16.
Describe2
the main limitation of using a nonexperimental variable in a study.
17.
Propose5
and justify6 expanding the simple experiment discussed in Objective
13 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
c.
Adding
a moderating factor