Statistical Models: Theory and Practice

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Cambridge University Press, Aug 8, 2005 - Mathematics - 414 pages
1 Review
This lively and engaging textbook provides the knowledge required to read empirical papers in the social and health sciences, as well as the techniques needed to build statistical models. The author explains the basic ideas of association and regression, and describes the current models that link these ideas to causality. He focuses on applications of linear models, including generalized least squares and two-stage least squares. The bootstrap is developed as a technique for estimating bias and computing standard errors. Careful attention is paid to the principles of statistical inference. There is background material on study design, bivariate regression, and matrix algebra. To develop technique, there are computer labs, with sample computer programs. The book's discussion is organized around published studies, as are the numerous exercises - many of which have answers included. Relevant papers reprinted at the back of the book are thoroughly appraised by the author.
 

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Contents

II
1
III
4
IV
6
V
9
VI
14
VII
18
VIII
28
IX
38
XXIV
99
XXV
106
XXVI
109
XXVII
123
XXVIII
142
XXIX
148
XXX
167
XXXI
169

X
41
XI
50
XII
52
XIII
55
XIV
57
XVI
64
XVII
65
XVIII
72
XIX
75
XX
81
XXI
82
XXII
88
XXIII
97
XXXII
180
XXXIII
184
XXXIV
185
XXXV
189
XXXVI
192
XXXVII
195
XXXVIII
200
XL
201
XLI
216
XLII
267
XLIII
283
XLIV
404
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About the author (2005)

David A. Freedman is Professor of Statistics at the University of California, Berkeley. He has also taught in Athens, Caracas, Jerusalem, Kuwait, London, Mexico City, and Stanford. He has written several previous books, including a widely used elementary text. He is one of the leading researchers in probability and statistics, with 150 papers in the professional literature. He is a member of the American Academy of Arts and Sciences. In 2003, he received the John J. Carty Award for the Advancement of Science from the National Academy of Sciences, recognizing his "profound contributions to the theory and practice of statistics." Freedman has consulted for the Carnegie Commission, the City of San Francisco, and the Federal Reserve, as well as several departments of the U.S. government. He has testified as an expert witness on statistics in law cases that involve employment discrimination, fair loan practices, duplicate signatures on petitions, railroad taxation, ecological inference, flight patterns of golf balls, price scanner errors, sampling techniques, and census adjustment.

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