Multiple Regression : A Primer (Undergraduate Research Methods & Statistics in the Social Sciences) [Paperback]

Paul D. Allison (Author)

Book Description

ISBN-10: 0761985336 | ISBN-13: 978-0761985334 | Publication Date: December 29, 1998 | Edition: 1

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.

Editorial Reviews

Review

"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 )

About the Author

Paul D. Allison is Professor of Sociology at the University of Pennsylvania, where he teaches advanced graduate courses on event history analysis, categorical data analysis, and structural equation models with latent variables. He is the author of seven books and more than 50 journal articles. Every summer he teaches 5-day workshops on survival analysis and logistic regression analysis that draw about 100 researchers from around the U.S.  A former Guggenheim Fellow, Allison received the 2001 Lazarsfeld Award for distinguished contributions to sociological methodology.

Product Details

• Paperback: 224 pages
• Publisher: Pine Forge Press; 1 edition (December 29, 1998)
• Language: English
• ISBN-10: 0761985336
• ISBN-13: 978-0761985334
• Product Dimensions: 9.1 x 6.2 x 0.5 inches
• Shipping Weight: 8.8 ounces (View shipping rates and policies)
• Average Customer Review: 4.3 out of 5 stars  See all reviews (9 customer reviews)
• Amazon Best Sellers Rank: #9,481 in Books (See Top 100 in Books)

More About the Author

Paul D. Allison, Ph.D., is Professor of Sociology at the University of Pennsylvania, and President of Statistical Horizons LLC. You can visit his website at www.StatisticalHorizons.com. After completing doctoral work in sociology at the University of Wisconsin, he did postdoctoral study in statistics at the University of Chicago and the University of Pennsylvania. He has published eight books and more than 60 articles on topics that include linear regression, log-linear analysis, logit analysis, probit analysis, measurement error, inequality measures, missing data, Markov processes, and event history analysis. Much of his earlier research was focused on career patterns of academic scientists. At present, his principal methodological research is focused on the analysis of longitudinal data, especially with determining the causes and consequences of events, and on methods for handling missing data. Each summer he teaches 5-day workshops on survival analysis and logistic regression analysis that draw about 90 doctorate-level researchers from around the U.S. At Penn, he teaches advanced graduate courses on event history analysis, categorical data analysis, and structural equation models with latent variables. A former Guggenheim Fellow, Allison received the 2001 Lazarsfeld Award for distinguished contributions to sociological methodology. In 2010, he was elected as a Fellow of the American Statistical Association.

Customer Reviews

Most Helpful Customer Reviews

25 of 25 people found the following review helpful:

5.0 out of 5 stars Great Intro Text for Research Training, April 17, 2005

By 

Puff (CHICAGO, ILLINOIS United States) - See all my reviews

This review is from: Multiple Regression : A Primer (Undergraduate Research Methods & Statistics in the Social Sciences) (Paperback)

This book was required for a graduate Sociology class in Survey Analysis. I began studying statistics the previous quarter and had a terrible time. The books were dry and uninteresting. This one is written in almost conversational English with plenty of examples and excellent explanations. The writing is clear and easy to follow. I read one or two chapters in a sitting with no problem (my eyes didn't glaze over and I didn't fall asleep.)

If you've ever used "The Complete Idiot's Guide to... " or "... for Dummies" series then you have some idea what this book is like; not that it's dumbed down at all, but that it's written in "plain English" that's easy to follow and (after my last class) literally a pleasure to read. I've been reading the book for 3 days and I am grasping concepts that I could not get in 10 weeks of studying with other texts.

Roughly speaking, the first half introduces the reader to the practice and application of regressions. The second half explains more of the technical details (the arithmetic, assumptions, etc.) The final chapters deal with some of the pitfalls and other considerations involved in using regressions (multi-collinearity, etc.) It's all been very helpful. I highly recommend this book to students of statistics and to instructors in need of texts for their courses.

6 of 6 people found the following review helpful:

5.0 out of 5 stars regression made easy, June 16, 2006

By 

John Berlinck (Texas) - See all my reviews

This review is from: Multiple Regression : A Primer (Undergraduate Research Methods & Statistics in the Social Sciences) (Paperback)

For social scientists, this book is so full of practical information about what to look out for in regression, and it's a well written, easy reading style...highly recommended. It's orientation is toward application including brief instructions for SPSS procedures. Another benefit is 5 different examples of how infomation is typically presented in social sciences journals including what are typical levels of sig. and explained variation. Note -- if you're looking for a lot of detailed underlying math or theory, this probably isn't your book.

5 of 5 people found the following review helpful:

5.0 out of 5 stars Great for learning the mechanics of regression, October 10, 2007

By 

H. Tubbs (Philadelphia, PA USA) - See all my reviews
(REAL NAME)   

This review is from: Multiple Regression : A Primer (Undergraduate Research Methods & Statistics in the Social Sciences) (Paperback)

This is hands-down the most helpful book I have come across in my graduate studies on regression. It's written in non-technical language and is very clearly organized. The book is a great introduction to the mechanics of regression-I find myself going back to it time and again when I am need a refresher or am having a problem in my analyses and need some basic help. Highly recommended for social science grad students.