Linear Regression with SPSS
This tutorial demonstrates step-by step methods for running a simple linear regression in SPSS. Linear regression uses the values of one or more predictive variables, known as independent variable to predict the value of a dependent or response variable. This is sometimes referred to creating a linear model since the resulting equation of a line can be used to predict values of the dependent variable.
Linear regression relies on a number of assumptions to create a valid model.
Regression Assumptions
- variables being evaluated are on a continuous scale
- a linear relationship exists
- errors are not auto correlated
- errors are approximately normally distributed
- the dataset contains no outliers
- variance of erros is roughly constant
This tutorial demonstrates both running the regression model and testing the regression assumptions to ensure model validity.
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