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Psychology 242
Research in Psychology
Dr. David J. McKirnan

Week 13.
Multiple Independent Variables.

Lecture notes

Multiple independent variables, factorial designs, interactions.

.Key topic: Main effects v. Additive effects v. Statistical interactions.

Lecture notes are here.


Chapter 8 and articles on studies addressing multiple variables: Stressful life events, genetic dispositions, and vulnerability for Depression (click here for full article), Gender differences in responses to alcohol, and the effect of attitudes and drugs on Sexual risk, .

Discussion group Assignment

(Click for a Word copy of Week 13 assignment).

Correlation coefficients: Going beyond your paper statistics.

For this week you will do a correlation.  This is not actually your statistics for your paper: doing an experiment (or quasi-experiment) calls for a t-test, and you did that last week.  We want you to compute a correlation so you really understand how this approach asks a different question than the t-test does. 

Here is another version of the data we have been using as an example: these data tables show two variables measured for each of eight students.  The question here concerns how the two variables relate to each other within participants; do participants who ended up with a lower score on Fear and Loathing of Statistics actually do better on a quiz later on?  Your t-test assignment last week examined differences between different groups of participants.

The first table contains scores attitudes toward statistics; the second table gives grades on a statistics quiz, both as a letter and a number.  The participants are the same in each table. Recall how to compute a correlation:

  1. r formulaCalculate the mean [M] and standard deviation [S] for each variable;
  2. Use those to compute a Z score for each participant on each variable, showing how far each person is from the M on that variable;
  3. Multiply each person’s Z score on Variable 1 by their Z score on Variable 2 to show how far they are from the M on the two variables
  4. Sum the products of the Z scores, divide by df: 

The tables on the next page show calculations for the Z scores for each participant on each variable (the actual Z scores are given in the last column).  For this assignment:

Statistics notes # 1