Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Statistics

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Michael J. Crawley 作者
Wiley
譯者
2005-4-22 出版日期
342 頁數
USD 52.00 價格
Paperback
叢書系列
9780470022986 圖書編碼

Statistics 在線電子書 圖書標籤: R  統計  編程  統計學  programming  Statistics  統計  statistics   


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Statistics 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Statistics 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



Statistics 在線電子書 用戶評價

評分

R用的好順溜但是講的不夠明白。

評分

清楚易懂

評分

我對R也不瞭解,對統計也一知半解,不過覺得這本書很不錯,代碼解釋很清楚,重要的統計學原則也有講。這本書射擊的統計學都是經典的統計檢驗和綫性模型,還是很入門的。

評分

清楚易懂

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清楚易懂

Statistics 在線電子書 著者簡介


Statistics 在線電子書 著者簡介


Statistics 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Statistics 在線電子書 圖書描述

Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing.

* Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology.

* Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data.

* The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing.

* Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.

* Includes numerous worked examples and exercises within each chapter.

* Accompanied by a website featuring worked examples, data sets, exercises and solutions:

http://www.imperial.ac.uk/bio/research/crawley/statistics

Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

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