Applied Regression: An Introduction (Quantitative Applications in the Social Sciences)

Michael S. Lewis-Beck

ISBN 10: 0803914946 / ISBN 13: 9780803914940

Published by SAGE Publications, Inc, Thousand Oaks, CA, 1980

About this Item

Spine faded, otherwise like new inside and out. Will be bubble-wrapped and carefully packed in a sturdy box to ensure safe transit. Seller Inventory # ABH3219

Bibliographic Details

Title: Applied Regression: An Introduction (...

Publisher: SAGE Publications, Inc, Thousand Oaks, CA

Publication Date: 1980

Binding: Soft cover

Condition: Fine

Dust Jacket Condition: No Jacket As Issued

About this title

Synopsis:

Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.

Review:

This is one of the best resources on basic regression techniques available on the market today. It remains my go-to guide for my own research. It is the quintessential text for graduate students pursuing degrees in the quantitative social sciences. This text has helped train several generations of social science researchers over the course of the last four decades. (Matt Vogel)

Lewis-Beck is hands-down the best introduction to linear regression that I have ever encountered.  I have used Lewis-Beck for 20 years – almost every year – in my methods courses. He really produced something special. For undergraduates and graduate students the treatment is clear and concise.  He is the only research methods title for which I offer no apology for assigning.  (Ross Miller)

For an introduction to regression for beginning graduate students or advanced undergraduates, the text is an excellent supplement to a more technical text that is capable of going into greater detail.... The book accomplishes what it sets out to do very well, which is to gently introduce audiences to the logic and basic mathematics of regression. (Carl L. Palmer)