Models for Probability and Statistical Inference 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Models for Probability and Statistical Inference

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James H. Stapleton 作者
Wiley-Interscience
译者
2007-12-17 出版日期
464 页数
USD 116.95 价格
Hardcover
丛书系列
9780470073728 图书编码

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Models for Probability and Statistical Inference 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

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Models for Probability and Statistical Inference 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Models for Probability and Statistical Inference 在线电子书 图书描述

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers

Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.

Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression.

Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

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