Mathematical Primer for Social Statistics

ISBN-10: 1412960800

ISBN-13: 9781412960809

Edition: 2009

Authors: John Fox

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Description:

A Mathematical Primer for Social Statistics: Beyond the introductory level, learning and effectively using statistical methods in the social sciences requires some knowledge of mathematics. It is, however, surprising how far one can go with a relatively modest mathematical background. The proposed monograph aims to provide that background, introducing the areas of mathematics that are most centrally important to applied social statistics: matrices, linear algebra, and vector geometry; basic differential and integral calculus, including multivariable and matrix calculus, and the application of calculus to optimization problems; and probability and estimation, including the basics of probability theory, discrete and continuous random variables, commonly encountered statistical distributions, principles of estimation, the method of maximum likelihood and the basics of Bayesian inference.It would be advantageous to cover all these topics in a single book.The expected readership includes advanced undergrads, graduate students, and researchers in the social sciences who wish to learn and use relatively advanced statistical methods, especially regression type of analysis, but whose mathematical preparation for this work is insufficient. There should be a potentially large market. The title should be able to stand alone or bundled together with our existing numbers in two ways: it could go together with many of the volumes on regression analysis, and it could also help fill the gap in foundation with our existing numbers on matrix algebra and calculus. I expect it will do better in the former role of bundling together with existing volumes on regression.
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Book details

List price: $22.00
Copyright year: 2009
Publisher: SAGE Publications, Incorporated
Publication date: 7/29/2008
Binding: Paperback
Pages: 184
Size: 5.50" wide x 8.50" long x 0.50" tall
Weight: 0.484
Language: English

John Fox is the Senator William McMaster Professor of Social Statistics in the Sociology Department of McMaster University in Hamilton, Ontario, Canada. Professor Fox earned a Ph.D. in sociology from the University of Michigan in 1972. He has delivered numerous lectures and workshops on statistical topics, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the annual meetings of the American Sociological Association, and the Oxford Spring School in Quantitative Methods for Social Research. He has written many articles on statistics, sociology, and social psychology, and is the author of several books on statistics, including most recently Applied Regression Analysis and Generalized Linear Models, Second Edition (Sage, 2008) and A Mathematical Primer for Social Statistics (Sage, 2009), and (with Sanford Weisberg) An R Companion to Applied Regression, Second Edition (Sage, 2011). Professor Fox is an active contributor to the R Project for Statistical Computing and is a member of the R Foundation. His work on this book was partly supported by a grant from the Social Sciences and Humanities Research Council of Canada..

Series Editor Introduction
Preface
Matrices, Linear Algebra, Vector Geometry
An Introduction to Calculus
Probability and Estimation
Putting the Math to Work
References
Index
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