Guide to using the learning objectives

Learning Objectives for Chapter 10-- The Simple Experiment



Pages 363-381


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 381-389


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 389-392


14.                       Explain2 how steps you take to increase your experiment's power could harm your experiment's external validity. Then, explain2 how steps you take to increase your experiment's external validity could harm your experiment's 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 experiment's power could harm your experiment's construct validity. Then, explain2 how steps you take to increase your experiment's construct validity could harm the experiment's power.

17.                       Explain2 how steps you take to make your experiment more ethical could harm the experiment's power. Then, explain2 how steps you take to increase your experiment's 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 392-400



19.                       Defend4 the following comment: "The average score of the experimental group is an estimate of what the average score would have been had all your participants received the treatment."

20.                       Explain2why the following statement is true: "The mean for the treatment group could be higher than the mean for the no-treatment group even if the treatment had no effect."

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 400-406


24.                       State1the basic idea behind the t  test.

25.                       You find the following on a computer printout of a t test analysis:  "df = 12, t = 5, p <.05, treatment group mean = 11, control group mean = 1, standard error of the difference between means =2."

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 Box 10-2). Using the effect size you calculated, assess6 whether the treatment had a large, medium, or small effect.


26.                       Referring to the concept of effect size, explain2 the difference between statistical significance and practical significance (having an important effect).



Pages 406-410


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.




Guide to using the learning objectives

Chapter Objectives Menu

Chapter 10 Menu

Research Design Explained Home page