PSYC09H3 Chapter Notes - Chapter 1: Confidence Interval, Sampling Error, Observational Error
Document Summary
Majorly used for prediction and casual analysis. Casual analysis: independent variables are regarded as causes of criterion (dependent variable) determine whether a particular independent variable really affects the dependent variable, and to estimate the magnitude of that effect, if any. Multiple regression: statistical method for studying the relationship between a single dependent variable (criterion) and one or more independent (predictor) variables. Least squares = method used to estimate the regression equation. Multiple = two or more independent variables. Linear = kind of equation that is estimated by the multiple regression method. For prediction studies, multiple regression makes it possible to combine many variables to produce optimal predictions of the dependent variable. For casual analysis, multiple regression separates the effects of independent variables on the dependent variable so that you can examine the unique contribution of each variable. Means it is based on a linear equation if you graph the equation you should get a straight line.
