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.

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.