9780813399713-0813399718-Understanding Multivariate Research: A Primer for Beginning Social Scientists

Understanding Multivariate Research: A Primer for Beginning Social Scientists

ISBN-13: 9780813399713
ISBN-10: 0813399718
Edition: 1
Author: Berry, William, Sanders, Mitchell
Publication date: 2000
Publisher: Routledge
Format: Paperback 87 pages
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Book details

ISBN-13: 9780813399713
ISBN-10: 0813399718
Edition: 1
Author: Berry, William, Sanders, Mitchell
Publication date: 2000
Publisher: Routledge
Format: Paperback 87 pages

Summary

Acknowledged authors Berry, William, Sanders, Mitchell wrote Understanding Multivariate Research: A Primer for Beginning Social Scientists comprising 87 pages back in 2000. Textbook and eTextbook are published under ISBN 0813399718 and 9780813399713. Since then Understanding Multivariate Research: A Primer for Beginning Social Scientists textbook was available to sell back to BooksRun online for the top buyback price of $ 1.26 or rent at the marketplace.

Description

Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a student's second year. William Berry and Mitchell Sanders's Understanding Multivariate Research fills this gap with a concise introduction to regression analysis and other multivariate techniques. Their book is designed to give new graduate students a grasp of multivariate analysis sufficient to understand the basic elements of research relying on such analysis that they must read prior to their formal training in quantitative methods. Berry and Sanders effectively cover the techniques seen most commonly in social science journals--regression (including nonlinear and interactive models), logit, probit, and causal models/path analysis. The authors draw on illustrations from across the social sciences, including political science, sociology, marketing and higher education. All topics are developed without relying on the mathematical language of probability theory and statistical inference. Readers are assumed to have no background in descriptive or inferential statistics, and this makes the book highly accessible to students with no prior graduate course work.

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