This tutorial walks you through a complete multiple regression analysis in SPSS:

• Data Checks and Descriptive Statistics
• SPSS Regression Dialogs
• SPSS Multiple Regression Output
• Multiple Regression Assumptions
• APA Reporting Multiple Regression

Quick guide on creating dummy variables in SPSS for categorical predictors in regression.

Intermediate tutorial with practice data, examples and a handy tool.

How to run and interpret dummy variable regression in SPSS?

These 3 examples walk you through everything you need to know.

Categorical variables can't readily be used as predictors in regression analysis; they must be split up into dichotomous variables known as “dummy variables”.

This tutorial offers a super easy tool for creating these.

"I'd like to mean center a lot of variables in order to compute interaction terms for a regression analysis. Is there an easy way to do this for many variables simultaneously?"

This simple SPSS tool creates one, many or all scatterplots among a set of variables.

Optionally, it adds (non)linear fit lines and regression tables as well.

SPSS stepwise regression example. Easy-to-follow explanation of what and why with downloadable data file and annotated output.

SPSS stepwise regression analysis in normal language. With illustrations, downloadable practice data and syntax.

Multiple regression is a statistical technique that aims to predict a variable of interest from several other variables. This tutorial explains multiple regression in normal language with many illustrations and examples.

This tutorial walks you through several simple options for creating scatterplots with regression lines.

We'll also cover linear and nonlinear regression lines for all cases or subgroups of cases.

Logistic regression is a technique for predicting a dichotomous outcome variable from 1+ predictors.

This simple introduction quickly walks you through all logistic regression basics with a downloadable example analysis.