Reference no: EM133382141
Ch. 8: Experimental Design:
What does it mean when two variables are confounded?
Describe an example of an experiment where variables are confounded in a way that makes the results difficult to interpret.
Explain the difference between internal and external validity. What kinds of problems in experiments are threats to each type?
Distinguish between a posttest-only, pretest-posttest, Soloman four-group, repeated measures, and matched pairs design.
What are the advantages of using a pretest-posttest design over a posttest-only design?
Define what "mortality" means in the context of experimental research, and explain why this is a problem.
Describe the difference between an independent groups design and a repeated measures design, using an example.
What are the advantages of a repeated measures design, compared with an independent groups design? What are the disadvantages?
Explain how practice, fatigue, and carryover effects can interfere with results in a repeated measures design. Use examples.
Name and describe a procedure for controlling for possible order effects in an experiment.
Describe the procedure for conducting a matched pairs design, and explain why you would do this.
Ch. 9: Conducting Experiments:
Describe the difference between a straightforward and staged manipulation, using examples.
What is a confederate? Why are they used in psychological research?
What are some important considerations in deciding how to manipulate the independent variable in an experiment?
Discuss the overall dilemma regarding the strength of the independent variable manipulation. Why would you want to make the manipulation as strong as possible? Why wouldn't you?
Describe and give examples of self-report, behavioral, and physiological measures of dependent variables.
Explain what is meant by a "ceiling" or "floor" effect in measuring the dependent variable. Describe an example of a study that might produce a ceiling effect. Give another example for a floor effect.
What are demand characteristics, and how can they be avoided? (For example, what is a placebo, and what is it for?)
Discuss possible sources of experimenter bias. Why are these important, and how can they be avoided?
What is the purpose of a manipulation check?
Ch. 10: Complex Experimental Designs:
What is a curvilinear relationship, and why is a complex experimental design necessary to identify this pattern?
Explain the general concept of a factorial design. What is done here, and why?
How are factorial designs labeled (i.e. what does a "2 x 3 factorial design" mean)?
Describe an example of a factorial design, such as the one summarized on p. 210-211 of your text. How do you identify a main effect of either variable? How do you identify an interaction?
Be able to identify a 3 x 3, 2 x 2, or 2 x 3 factorial design from a verbal description of an experiment (such as the designs in Handout 4).
What is an IV x PV design? Be able to identify PVs in a verbal description of an experiment (such as the designs in Handout 4).
In a 2 x 2 factorial design, in terms of possible outcomes: what are the three comparisons you would do/questions you would answer? (see Ch. 10 Powerpoint, Slide 12)
Practice working with data from a 2 x 2 factorial design, such as Outcome 1 and Outcome 2 on Handout 5 (HW on Outcomes of Factorial Designs). How can you use these numbers to determine whether there are main effects, or interactions?
When given a verbal description of an experiment with more than two independent variables, be able to identify the design (ex: 3 x 2 x 3).
How do you calculate the number of conditions in a factorial design (for example, how many conditions are there in a 2 x 3 x 3 design)?
Imagine conducting the same experiment as an independent groups, repeated measures, or mixed factorial design. How does the decision of what design to use affect the number of participants you will need?
Ch. 11: Single-Case, Quasi-Experimental, and Developmental Research:
State the key difference between true experimental designs and quasi-experimental designs.
Explain how an ABA, ABAB, multiple-baseline, or control series design all help rule out alternative explanations.
What is meant by a multiple-baseline design across subjects, or across situations? Provide examples.
What is a reversal design? Describe an example, and explain and what the purpose is of doing it this way.
Give an example of a one-group posttest-only design, and explain why these results cannot be interpreted.
Describe and give examples of a one-group pretest-posttest design and a nonequivalent control group design, explaining the advantages and problems with each one.
Explain how history, maturation, testing, and instrument decay are all potential problems for interpreting the results of a one-group pretest-posttest design.
What is regression towards the mean, and why does this occur?
Discuss the interrupted time series design, and explain why it is valuable for interpreting whether a particular intervention had an effect.
Give examples of cross-sectional, longitudinal, and sequential designs, and summarize the pros and cons of each type.
What is a cohort? Why is this concept important in developmental research?