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Probability and Statistical Inference

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Mukhopadhyay, Nitis 作者
CRC Press
译者
2000 出版日期
665 页数
$ 116.33 价格
丛书系列
9780824703790 图书编码

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发表于2024-11-05


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

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

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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因为习题没有答案, 所以被professor选成教材.... 排版太差了, 如果自己看的话还是看the red book吧, 至少习题答案很容易找到.

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因为习题没有答案, 所以被professor选成教材.... 排版太差了, 如果自己看的话还是看the red book吧, 至少习题答案很容易找到.

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Probability and Statistical Inference 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Probability and Statistical Inference 在线电子书 图书描述

Priced very competitively compared with other textbooks at this level! This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts.Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, "Probability and Statistical Inference": studies the Helmert transformation for normal distributions and the waiting time between failures for exponential distributions; develops notions of convergence in probability and distribution; spotlights the central limit theorem (CLT) for the sample variance; introduces sampling distributions and the Cornish-Fisher expansions; concentrates on the fundamentals of sufficiency, information, completeness, and ancillarity; explains Basu's Theorem as well as location, scale, and location-scale families of distributions; and, covers moment estimators, maximum likelihood estimators (MLE), Rao-Blackwellization, and the Cramer-Rao inequality.This book: discusses uniformly minimum variance unbiased estimators (UMVUE) and Lehmann-Scheffe Theorems; focuses on the Neyman-Pearson theory of most powerful (MP) and uniformly most powerful (UMP) tests of hypotheses, as well as confidence intervals; includes the likelihood ratio (LR) tests for the mean, variance, and correlation coefficient; summarizes Bayesian methods; describes the monotone likelihood ratio (MLR) property; handles variance stabilizing transformations; provides a historical context for statistics and statistical discoveries; and, showcases great statisticians through biographical notes. Employing over 1400 equations to reinforce its subject matter, "Probability and Statistical Inference" is a groundbreaking text for first-year graduate and upper-level undergraduate courses in probability and statistical inference who have completed a calculus prerequisite, as well as a supplemental text for classes in Advanced Statistical Inference or Decision Theory.

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