Multiple Regression: A Primer

Allison, Paul D.

ISBN 10: 0761985336 ISBN 13: 9780761985334
Verlag: Sage Publications, Inc, 1999
Gebraucht Paperback

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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.

Über die Autorin bzw. den Autor: Paul D. Allison, Ph.D., is Professor of Sociology at the University of Pennsylvania where he teaches graduate courses in methods and statistics. He is also the founder and president of Statistical Horizons LLC which offers short courses on a wide variety of statistical topics.

After completing his doctorate 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, logistic regression, structural equation models, inequality measures, missing data, and survival analysis.

Much of his early research focused on career patterns of academic scientists. At present, his principal research is on methods for analyzing longitudinal data, especially those for determining the causes and consequences of events, and on methods for handling missing data.

A former Guggenheim Fellow, Allison received the 2001 Lazarsfeld Award for distinguished contributions to sociological methodology. In 2010 he was named a Fellow of the American Statistical Association. He is also a two-time winner of the American Statistical Association's award for "Excellence in Continuing Education."

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Bibliografische Details

Titel: Multiple Regression: A Primer
Verlag: Sage Publications, Inc
Erscheinungsdatum: 1999
Einband: Paperback
Zustand: Very Good
Zustand des Schutzumschlags: No Jacket

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