PSY 2116 Study Guide - Final Guide: Repeated Measures Design, Interval Ratio, Dependent And Independent Variables

• School: University of Ottawa
• Department: Psychology
• Course: PSY 2116
• Professor: Meredith Rocchi

Document Summary

Correlation: interval data predicting interval data with no cause-and-effect relationship. Multiple regression: more than interval independent variable predicting a dependent variable. Independent t-test: two categorical variables predicting an interval/ratio, different people. Repeated t-test: two catergorical variables predicting an interval/ratio, same people. Independent anova: one categorical variable (with 3+ levels) predicting interval/ratio, different people. Independent factorial anova: two or more categorical variables predicting interval/ratio, different people. Repeated measures anova: one categorical variable (with 3+ levels) predicting interval/ratio, the same people are tested multiple times. Repeated measures factorial anova: two or more categorical variables predicting interval/ ratio, the same people are tested multiple times. Mixed factorial anova: one independent categorical variable and one repeated measures categorical variable predicting an interval/ratio dependent variable. Is there a relationship between variable a and variable b? . 2. linearity (graphs: chart builder: scatterplot) two variables measured at the interval or ratio level.