Guide to using the learning objectives
1.
List1and
define1 three criteria you must satisfy in order to infer causality.
2.
Imagine
that you want to design a study looking at the effects of surfing the Internet on
self-esteem. Outline3 the
role each of the following would play as you design your study:
a.
covariation
b. temporal precedence
c.
spuriousness.
3.
Compare4
and contrast4 how a simple, two-group, between-subjects
experiment and a single-n experiment would deal with covariation,
temporal precedence, and spuriousness.
4.
Design5a
single-n experiment.
5.
Using
the single-n experiment you generated in Objective 4, illustrate3how
you could establish a stable baseline.
6.
Describe2the
A-B design. Explain2 why it is necessary to establish a stable baseline
in A-B design. Describe2 two threats to the validity of an A-B
design.
7.
Describe2each
of the following variations on the A-B design:
a.
the reversal design
b. psychophysical designs
c.
the multiple-baseline design.
8.
Design5each
of the following:
a.
the reversal design
b. a psychophysical design
c.
the multiple-baseline design.
9.
Explain2
why the A-B-A design has more internal validity than the A-B design.
Provide3three reasons that behavior in an A-B-A design may not
return to baseline after the treatment is withdrawn.
10.
Compare4
and contrast4 single-n designs in terms of (a) internal
validity and(b) construct validity.
11. List1two reasons why people tend to question the external validity of single-n designs. Then, defend4 the statement: "Single-n designs can have external validity."
12.
Evaluate6
single-n designs on each of the following criteria:
a.
internal validity
b. construct validity
c.
external validity.
13.
Describe2 two conditions in which single-n
designs are most likely to be useful.
14.
Define1quasi-experiment.
Distinguish4 between quasi-experiments and experiments.
15.
Outline3
the "spurious eight" threats to internal validity. Classify4the
spurious eight into three categories: nontreatment
factors that cause participants to change, measurement errors that can
masquerade as treatment effects, and nontreatment
differences between treatment and no-treatment groups.
16.
Describe2
steps you could take to combat each of the eight threats to internal
validity.
17.
Describe2
the pretest-posttest design. Contrast4
this design with the A-B single-n design. List1the threats to
internal validity that this design eliminates. Explain2 how it
eliminates these threats.
18.
Compare4
and contrast4 the time-series design with the pretest-posttest
design. Explain2 why the time-series design is less vulnerable to maturation
and regression than the pretest-posttest design.
19.
Propose5a
study that uses a time-series design.
20.
Illustrate3how
the time-series design could estimate the effects of maturation.
21.
Name1the
biggest threat to a time-series design's internal validity. Explain2 why
that threat is so serious.
22.
For
the time-series study you generated before (in Objective 19), propose5 methods
for minimizing each of the following threats to internal validity:
a.
instrumentation
b. mortality
c.
testing
d. maturation
e. history
f.
regression.
23.
Revise4
your time-series study to make it a study that uses a reversal
time-series design. Discuss2 the advantages and disadvantages of
making this change to your original time-series study.
24. Revise4 your original time-series study to make it a study that uses a two-group time-series design. Discuss2 the advantages and disadvantages of making this change to your original time-series study.
25.
Outline3
the difference(s) between a simple experiment and a nonequivalent
control-group design.
26.
Explain2
why some argue that the no-treatment group in the non-equivalent
control-group design should not be called a control group.
27.
Explain2
why matching your groups may not make your treatment and no-treatment
groups equivalent. Be sure to include the terms selection by maturation
interaction and regression in your answer.
28.
Define1law
of parsimony. Explain2 how quasi-experimenters use this law.