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Multiple Regression

Multiple Regression
A Primer

  • Paul D. Allison - University of Pennsylvania, University of Pennsylvania, USA

February 1999 | 224 pages | SAGE Publications, Inc
Multiple regression is at the heart of social science data analysis, because it deals with explanations and correlations. This book is a complete introduction to this statistical method.

This textbook is designed for the first social statistics course a student takes and, unlike other titles aimed at a higher level, has been specifically written with the undergraduate student in mind.

What Is Multiple Regression?
How Do I Interpret Multiple Regression Results?
What Can Go Wrong with Multiple Regression?
How Do I Run a Multiple Regression?
How Does Bivariate Regression Work?
What Are the Assumptions of Multiple Regression?
What Can Be Done about Multicollinearity?
How Can Multiple Regression Handle Nonlinear Relationships?
How Is Multiple Regression Related to Other Statistical Techniques?

"I find the concept for this approach to teaching undergraduate research methods and statistics innovative and exciting. The idea of ‘core’ texts supplemented by satellite volumes covering specific, important topics makes absolute sense." 

Barbara Heyl
Illinois State University

This book is an excellent reference for applied researchers. Particularly for those who wants to work with multi-variable prediction problem.

Dr Anshuman Sharma
International Business Administration, College of Applied Sciences, Ministry of Higher Education
May 26, 2015

Allison gives a great basic understanding to the conceptual element of regression analysis.

Ms Megan Haak
Ed Policy Community Stds Dept, University of Wisconsin - Milwaukee
August 6, 2011

This is a well written and accessible book on the core issues relating to using regression analysis. It is well laid out with unambiguous explanations about why proceedures are as they are. Something in there for both the newbie and those who think they already know it all. I will be recommending it to all of my students who take courses on regression.

Dr Alex Sutherland
Institute of Criminology, Cambridge University
January 26, 2011

The accessible language and simple format is ideal for students with little mathematical background.

Professor Joe Grengs
College Of Arch Urban Planning, University of Michigan
December 14, 2010

Allison's book presents relevant information on multiple regression at a level that is easily digestible for students.

Professor Dale Willits
Sociology Dept, University of New Mexico
April 13, 2010

Easy to read. A good primer

Malina Monaco
Education Dept, North Carolina State University
January 25, 2010

Sample Materials & Chapters


Chapter 1

Chapter 3

Data Set

For instructors

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