CMN 3102 Lecture Notes - Lecture 11: Total Variation, Multicollinearity, Analysis Of Variance

• School: University of Ottawa
• Department: Communication
• Course: CMN 3102
• Professor: Philippe Rousseau

Document Summary

Widely used to test research hypotheses: can test more than one research hypothesis simultaneously keeping all other factors constant. Variables at interval-ratio level: in practice, can also be used for ordinal variables if they are treated as interval- ratio, can be used for nominal variables only when they are transformed into dummy variables. Bivariate linear regression: examines the relationship between two variables. Multiple linear regression: examines the relationship between more than two variables. Can determine how much of the variable in the dependent variable is explained (predicted) by the independent variables. Which, if any, of the independent variables is a statistically significant predictor of the dependent variable. Def: the amount of change produced in the dependent variable by a unit change in an independent variable keeping other independent variables constant. Positive sign of regression coefficient: positive effect of the independent variable on the dependent variable. Negative sign of regression coefficient: negative effect of the independent variable on the dependent variable.