Guide to using the learning objectives
1. Define1 simple experiment.
Define1 independent random assignment. Explain2
why independent random assignment enables researchers to use the simple
experiment to make cause-effect statements.
2. Compare4 and contrast4
the following:
a. Experimental hypotheses and hypotheses
that do not postulate a cause-effect relationship.
b. Experimental hypothesis and null hypothesis
3. State1 what conclusions can
be drawn when
a. The null hypothesis is rejected
b. The null hypothesis is not rejected
4. Distinguish4 between
a. Independent variable and dependent variable
b. Control group and experimental group
5. Explain2 the implications
of the need to keep observations independent on
a. How participants are selected, and
b. How participants are treated.
6. Explain2 why the need for
random assignment means that some hypotheses cannot be tested in
a simple experiment.
7. Distinguish4 between what
statistically significant results mean and what they do not necessarily mean.
8. Explain2 why null results
do not prove the null hypothesis.
Pages 292-299
9. Define1 Type I error,
describe2what can be done to reduce the risk of making Type I
errors, and explain2 the tradeoff involved in trying to reduce Type
I errors.
10.
Define1Type
II error. Define power. Then, discuss2 the
relationship between Type II error and power. Finally, contrast4
Type II errors with Type I errors.
11.
Explain2
why reducing the extent to which random error affects your study will not reduce your risk of making a Type I
error.
12.
Explain2
why reducing the extent to which random error affects your study will
reduce your risk of making a Type II error.
13.
Describe2how
the risk of Type II errors can be reduced. In your answer, be sure to address
steps that will (a) reduce random error, (b) allow random error to balance out,
and (c) allow the effect to be detected even when there is a lot of random
error in your data.
Pages 299-302
14.
Explain2
how steps you take to increase your experimentÕs power could harm your experimentÕs
external validity. Then, explain2 how steps you take to increase
your experimentÕs external validity could harm your experimentÕs power.
15.
Explain2
how using placebo treatments and double-blind procedures could improve
the construct validity of a simple experiment.
16.
Explain2
how steps you take to increase your experimentÕs power could harm your experimentÕs
construct validity. Then, explain2 how steps you take to increase
your experimentÕs construct validity could harm the experimentÕs power.
17.
Explain2
how steps you take to make your experiment more ethical could harm the experimentÕs
power. Then, explain2 how steps you take to increase your
experimentÕs power could make your experiment less ethical.
18.
Rank6
the following in how important they should be in designing a simple
experiment: construct validity, ethics, external validity, and power. Justify6
your rankings.
Pages 302-308
19.
Defend4
the following comment: ÒThe average score of the experimental group is an
estimate of what the average score would have been had all your participants received
the treatment.Ó
20.
Explain2why
the following statement is true: ÒThe mean for the treatment group could be
higher than the mean for the no-treatment group even if the treatment had no
effect.Ó
21.
Examine4why,
in the simple experiment, each of the following is true:
a. random error causes scores within each
group to differ from one another.
b. random error may cause the experimental
group means to differ from the control group mean.
22.
The
means of your experimental and control groups differ. Outline3 the factors that a
statistical test would use to determine whether the difference between the
means is large enough to be due to the treatment rather than to chance alone.
Examine4 the role of the following in your answer:
a. The size of the difference between your
two group means,
b. The amount of variability within each
of your groups, and
c. The number of participants in each
of your groups.
23.
Choose1which
of the following experiments illustrates a difference between the experimental
and control groups that is most likely to be due to more than chance alone.
Defend4 your choice.
Experiment A Experiment
B
Control Experimental Control Experimental
4 8 8 12
5 10 10 15
6 10 12 16
3 10 6 13
4 14 8 18
5 16 10 21
Pages 309-313
24.
State1the
basic idea behind the t test.
25.
You
find the following on a computer printout of a t test analysis: Òdf
= 12, t = 5, p <.05, treatment group mean = 11, control group
mean = 1, standard error of the difference between means =2.Ó
a. Determine3 the number of scores
the computer analyzed.
b. Determine3 whether the results
were statistically significant.
c. Show3 the numerator (top
part) and the denominator (bottom part) of the t ratio.
d. Compute3 an index of effect
size (see
26.
Referring
to the concept of effect size, explain2 the difference between statistical
significance and practical significance (having an important effect).
Pages 313-316
27.
List1the
two most essential assumptions that must be met to compute a meaningful t
test.
28.
List1two
less serious assumptions of the t test. Then, explain2 why
these assumptions are usually not a threat to conducting a meaningful t
test. In your answer, be sure to refer to the central limit theorem.
29.
List1
six questions to ask when results of your simple experiment are not statistically significant.
30.
List1
two questions to ask when results of your simple experiment are
significant.