Guide to using the learning objectives
1.
List1
and 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.
Design5
a single-n experiment.
5.
Using
the single-n experiment you generated in Objective 4, illustrate3
how you could establish a stable baseline.
6.
Describe2
the 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.
Describe2
each of the following variations on the A-B design:
a. the reversal design
b. psychophysical designs
c.
the
multiple-baseline design.
8.
Design5
each 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. Provide3
three 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the treatment is withdrawn.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.
List1
two 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.
Define1
quasi-experiment. Distinguish4 between quasi-experiments and experiments.
15.
Outline3
the “spurious eight” threats to internal validity. Classify4
the 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. List1
the 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.
Propose5
a study that uses a time-series design.
20.
Illustrate3
how the time-series design could estimate the effects of maturation.
21.
Name1
the 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.
Define1
law of parsimony. Explain2 how quasi-experimenters use this law.