SPSS Web Books
Regression with SPSS: Short Outline
by Xiao Chen, Phil Ender, Michael Mitchell & Christine Wells
(in alphabetical order)
The aim of these materials is to help you increase your skills in using regression analysis with SPSS. This web book does not teach regression, per se, but focuses on how to perform regression analyses using SPSS. It is assumed that you have had at least a one quarter/semester course in regression (linear models) or a general statistical methods course that covers simple and multiple regression and have access to a regression textbook that explains the theoretical background of the materials covered in these chapters. These materials also assume you are familiar with using SPSS, for example that you have taken the SPSS 1 & SPSS 2 classes or have equivalent knowledge of SPSS. If you are a member of the UCLA community and have questions about these materials, we welcome you to send questions via email to ATSstat@ucla.edu or to visit our consulting services .
You can find this book at https://stats.idre.ucla.edu/stat/spss/webbooks/reg/
Book Chapters
 Section 1: Regression Concepts
 Section 2: Categorical
Coding and Interactions in Depth
 Chapter 4 – Beyond Ordinary Least Squares Regression
 Chapter 5 – Additional coding systems for categorical variables in regression analysis
 Chapter 6 – More on interactions of categorical variables in regression analysis (under development)
 Chapter 7 – More on interactions of continuous and categorical variables in regression analysis (under development)
 Chapter 8 – Interactions of continuous variables in regression analysis (under development)
Book Chapters and Outline
 Chapter 1 – Simple and Multiple Regression
1.0 Introduction
1.1 A First Regression Analysis
1.2 Examining Data
1.3 Simple linear regression
1.4 Multiple regression
1.5 Transforming variables
1.6 Summary 
Chapter 2 – Regression Diagnostics
2.0 Regression Diagnostics
2.1 Unusual and Influential data
2.2 Tests on Normality of Residuals
2.3 Tests on Nonconstant Error of Variance
2.4 Tests on Multicollinearity
2.5 Tests on Nonlinearity
2.6 Model Specification
2.7 Issues of Independence
2.8 Summary 
Chapter 3 – Regression with Categorical Predictors
3.0 Regression with Categorical Predictors
3.1 Regression with a 0/1 variable
3.2 Regression with a 1/2 variable
3.3 Regression with a 1/2/3 variable
3.4 Regression with multiple categorical predictors
3.5 Categorical predictor with interactions
3.6 Continuous and Categorical variables
3.7 Interactions of Continuous by 0/1 Categorical variables
3.8 Continuous and Categorical variables, interaction with 1/2/3 variable
3.9 Summary  Chapter 4 – Beyond Ordinary Least Squares Regression

Chapter 5 – Additional coding systems for categorical variables in regression
analysis
4.1 Simple Coding
4.2 Forward Difference Coding
4.3 Backward Difference Coding
4.4 Helmert Coding
4.5 Reverse Helmert Coding
4.6 Deviation Coding
4.7 Orthogonal Polynomial Coding
4.8 UserDefined Coding
4.9 Summary  Chapter 6 – More on interactions of categorical variables in regression analysis (under development)
 Chapter 7 – More on interactions of continuous and categorical variables in regression analysis (under development)
 Chapter 8 – Interactions of continuous variables in regression analysis (under development)