Section 7.1

Fundamentals of Social Statistics by Adam J. McKee

Multiple Regression

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.

 


[ Back | Contents | Next ]

Last Modified:  06/04/2021

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.