Question

1. Identify the number of independent variables, the number of levels for each independent variable, and the total number of conditions for each of the following examples of complex design experiments:

(a) 2 H 3      (b) 3 H 3      (c) 2 H 2 H 3 (d) 4 H 3

2.   Identify the conditions in a complex design when the following independent variables are factorially combined: (1) type of task with three levels (visual, auditory, tactile) and (2) group of children tested with two levels (developmentally delayed, no delay).

3.   Use the Kassin et al. results in Table 8.3 (page 243 in text) for interrogators' efforts to obtain a confession to show there are two possible ways to describe the interaction effect.

4.   Describe how you would use the subtraction method to decide whether an interaction effect was present in a table showing the results of a 2 H 2 complex design.

5.   Describe the pattern in a line graph that indicates the presence of an interaction effect in a complex design.

6.   Outline the steps in the analysis plan for a complex design with two independent variables when there is an interaction effect and when there is not an interaction effect.

7.   Use an example to illustrate how a complex design can be used to test predictions derived from a psychological theory.  

8.   How is the external validity of the findings in a complex design influenced by the presence or absence of an interaction effect?

9.   Explain why researchers should be cautious about saying that an independent variable does not have an effect on behavior.

10. Describe the pattern of descriptive statistics that would indicate a ceiling (or floor) effect may be present in a data set, and describe how this pattern of data may affect the interpretation of inferential statistics (e.g., F-test) for these data.

Answer 1

1a. Number of independent variables = 2; Number of levels for each independent variable = IV1: 2 and IV2: 3; Total number of conditions = 6.

1b. Number of independent variables = 2; Number of levels for each independent variable = IV1: 3 and IV2: 3; Total number of conditions = 9.

1c. Number of independent variables = 3; Number of levels for each independent variable = IV1: 2, IV2: 2 and IV3: 3; Total number of conditions = 12.

1d. Number of independent variables = 2; Number of levels for each independent variable = IV1: 4 and IV2: 3; Total number of conditions = 12.

Please post the other questions separately as we are supposed to answer just one question or four subparts of a question