Ninth Edition CoverGraziano & Raulin
Research Methods (9th edition)

Chapter 10 Exercises
Single-Variable, Independent-Groups Designs

The following exercises are designed to give you hands-on practice of the skills learned in this chapter.

  1. Choose any research question that you find interesting (e.g., the relationship between anger and aggression). Describe a study on this research question using each of the research designs discussed in Chapter 10 (similar to what was done in the textbook chapter with the running example of hyperactivity and food additives). For each design, identify which confounding variables are controlled by the design and which are not.

  2. Listed below are hypothetical scores from a research study that employed three groups of participants. The mean score in the three groups should be compared using an analysis of variance. Using the formulas provided on this website or using SPSS for Windows, compute the F-ratio for these data. This will serve as a baseline for comparison in the following exercises.

    Group A Group B Group C
    104 91 129
    121 107 103
    93 99 117
    73 73 95
    109 86 114


    (a) You are now to take the numbers above and add 10 to each score in Group C and subtract 1 from each score in Group B. Before you re-compute the analysis of variance with this new set of data, ask yourself what type of variance you have changed with this procedure (i.e., between-groups variance or within-groups variance?). What effect should this have on the F-ratio (i.e., should the F-ratio increase or decrease? Will the differences between the groups be more or less significant?)? Now, re-compute the F-ratio to see if your ideas are correct.

    (b) Now take the original data and modify the data using the following procedure. Roll two dice, and determine the count showing. Then flip a coin: If the coin is heads, subtract the number showing on the dice from the score; if the coin is tails, add the number showing to the score. Continue this process for each and every score in all of the groups. Before you re-compute the analysis of variance with this new set of data, ask yourself what type of variance was affected by this manipulation (i.e., between-groups variance or within-groups variance?). What effect should this manipulation have on the F-ratio? Now, re-compute the analysis of variance with your revised data. Do the results confirm your expectation?

    (c) What do you think would happen if you took the original data set and repeated the process described in b above, but this time, instead of using two dice, you use a single die to determine how many points to add or subtract from each of the scores? Try it, and see whether your prediction is correct by comparing the results of the analysis with the original F-ratio and with the F-ratio computed in b above.

  3. For each of the following designs (i) give an example, (ii) identify the major threats to validity, and (iii) state the limits on the conclusions that can be drawn.
    a. Single-group, posttest-only design
    b.     Ex post facto design
    c. Single-group, pretest-posttest design
    d.     Pretest-posttest, natural control-group design

  4. For each of the following types of experimental design, (i) give an example and (ii) indicate what threats to validity are controlled.
    a.     Randomized, posttest-only, control-group design
    b.     Randomized, pretest-posttest, control-group design
    c.     Multilevel, completely randomized, between-subjects design