Statistics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Statistics

简体网页||繁体网页
Michael J. Crawley 作者
Wiley
译者
2005-4-22 出版日期
342 页数
USD 52.00 价格
Paperback
丛书系列
9780470022986 图书编码

Statistics 在线电子书 图书标签: R  统计  编程  统计学  programming  Statistics  統計  statistics   


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发表于2024-08-25


Statistics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Statistics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Statistics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



Statistics 在线电子书 用户评价

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基本无用。

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R用的好顺溜但是讲的不够明白。

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我对R也不了解,对统计也一知半解,不过觉得这本书很不错,代码解释很清楚,重要的统计学原则也有讲。这本书射击的统计学都是经典的统计检验和线性模型,还是很入门的。

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清楚易懂

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R用的好顺溜但是讲的不够明白。

Statistics 在线电子书 著者简介


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Statistics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Statistics 在线电子书 图书描述

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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