An Introduction to Statistical Inference and Its Applications with R 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


An Introduction to Statistical Inference and Its Applications with R

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Michael W. Trosset 作者
Chapman and Hall/CRC
譯者
2009-6-23 出版日期
496 頁數
USD 94.95 價格
Hardcover
叢書系列
9781584889472 圖書編碼

An Introduction to Statistical Inference and Its Applications with R 在線電子書 圖書標籤: 統計學  教材   


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An Introduction to Statistical Inference and Its Applications with R 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

An Introduction to Statistical Inference and Its Applications with R 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

An Introduction to Statistical Inference and Its Applications with R 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



An Introduction to Statistical Inference and Its Applications with R 在線電子書 用戶評價

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例子蠻多的,理論降低到最小化。特彆適閤考試,但沒什麼實用價值感覺。

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例子蠻多的,理論降低到最小化。特彆適閤考試,但沒什麼實用價值感覺。

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例子蠻多的,理論降低到最小化。特彆適閤考試,但沒什麼實用價值感覺。

評分

例子蠻多的,理論降低到最小化。特彆適閤考試,但沒什麼實用價值感覺。

評分

例子蠻多的,理論降低到最小化。特彆適閤考試,但沒什麼實用價值感覺。

An Introduction to Statistical Inference and Its Applications with R 在線電子書 著者簡介


An Introduction to Statistical Inference and Its Applications with R 在線電子書 著者簡介


An Introduction to Statistical Inference and Its Applications with R 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

An Introduction to Statistical Inference and Its Applications with R 在線電子書 圖書描述

Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples-not to perform entire analyses.After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference.Focusing on the assumptions that underlie popular statistical methods, this textbook explains how and why these methods are used to analyze experimental data.

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