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Multiple Linear Regression

Multiple linear regression is an extension of bivariate regression. It is used when we want to predict a continuous (interval or ratio) variable's value based on the value of more than one predictor variable, which can be any measurement scale (e.g., nominal, ordinal, interval, or ratio). In this session, Dr. Taylor discusses (1) the four scales of measurement, (2) describes the conditions for using multiple linear regression (with all continuous predictor variables), (3) identifies data assumptions surrounding multiple linear regression, (4) shows how to conduct multiple linear regression using SPSS, (5) explains SPSS output/results, and (6) shows how to write an APA-compliant results section based on the SPSS output, including appropriate tables and figures.