Previously, we learned that regression analysis can be used to predict the value of a variable Y given the value of a variable X. This is obviously a very useful tool for the social scientist attempting to explain, predict, and control social phenomena. A problem with this is that most social phenomena are very complex, and one predictor variable rarely does a very good job of predicting an outcome variable. Most social phenomena have multiple causes, and a mathematical model of those phenomena should consider multiple contributing factors. This deficiency is partially solved by multiple linear regression.
Multiple regression analysis is a statistical tool that allows the researcher to use two or more independent variables (Xs) to predict a single dependent variable (Y). Like the simple linear regression technique we learned earlier, multiple regression assumes that the relationship between X and Y is linear for all Xs.
Multiple Regression is a statistical technique that allows for the prediction of a single dependent variable Y with multiple independent variables.
Last Modified: 02/14/2019
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