A Course in Probability and Statistics

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Duxbury Press, 1996 - Mathematics - 838 pages
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This author's modern approach is intended primarily for honors undergraduates or undergraduates with a good math background taking a mathematical statistics or statistical inference course. The author takes a finite-dimensional functional modeling viewpoint (in contrast to the conventional parametric approach) to strengthen the connection between statistical theory and statistical methodology.

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Contents

Expectation
81
Special Continuous Models
134
chapter H Special Discrete Models
162
chapter J Dependence
209
Conditioning
274
chapter Normal Models
338
Introduction to Linear Regression
396
chapter u Linear Analysis
427
Orthogonal Arrays
579
chapter L Binomial and Poisson Models
635
Logistic Regression and Poisson Regression
673
Properties of Vectors and Matrices
751
Summary of Probability
760
Summary of Statistics
774
appendix U Hints and Answers
798
Tables
828

chapter IU Linear Regression
494
Copyright

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