國立虎尾科技大學 |

Univariate, bivariate, and multivariate statistics using R = quantitative tools for data analysis and data science /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Univariate, bivariate, and multivariate statistics using R/ Daniel J. Denis.
其他題名:	quantitative tools for data analysis and data science /
作者:	Denis, Daniel J.,
出版者:	Hoboken, NJ :John Wiley & Sons, : 2020.,
面頁冊數:	1 online resource (xvii, 366 p.) :ill. :
標題:	R (Computer program language) -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119549963
ISBN:	9781119549963

Univariate, bivariate, and multivariate statistics using R = quantitative tools for data analysis and data science /
Denis, Daniel J.,1974-

Univariate, bivariate, and multivariate statistics using Rquantitative tools for data analysis and data science /[electronic resource] :Daniel J. Denis. - 1st ed. - Hoboken, NJ :John Wiley & Sons,2020. - 1 online resource (xvii, 366 p.) :ill.

Includes bibliographical references and index.

Introduction to applied statistics -- Introduction to R and computational statistics -- Exploring data with R : essential graphics and visualization -- Means, correlations, counts : drawing inferences using easy-to-implement statistical tests -- Power analysis and sample size estimation using R -- Analysis of variance : fixed effects, random effects, mixed models and repeated measures -- Simple and multiple linear regression -- Logistic regression and the generalized linear model -- Multivariate analysis of variance (MANOVA) and discriminant analysis -- Principal components analysis -- Exploratory factor analysis -- Cluster analysis -- Nonparametric tests.

"This book provides a user-friendly and practical guide on R, with emphasis on covering a broader range of statistical methods than previous books on R. This is a "how to" book and will be of use to undergraduates and graduate students along with researchers and professionals who require a quick go-to source to help them perform essential statistical analyses and data management tasks in R. The book only assumes minimal prior knowledge of statistics, providing readers with the tools they need right now to help them understand and interpret their data analyses. This book covers univariate, bivariate, and multivariate statistical methods, as well as some nonparametric tests. It provides students with a hands-on easy-to-read manual on the wealth of applied statistics and essential R computing that they will need for their theses, dissertations, and research publications. A strength of this book is its scope of coverage of univariate through to multivariate procedures, while simultaneously serving as a friendly introduction to R software"--

ISBN: 9781119549963Subjects--Topical Terms:

679069
R (Computer program language)

LC Class. No.: QA279 / .D45776 2020

Dewey Class. No.: 519.5/302855133

Univariate, bivariate, and multivariate statistics using R = quantitative tools for data analysis and data science /
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020 $z 9781119549932 $q (hbk.)
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050 0 4 $a QA279 $b .D45776 2020
082 0 0 $a 519.5/302855133 $2 23
100 1 $a Denis, Daniel J., $d 1974- $3 1342734
245 1 0 $a Univariate, bivariate, and multivariate statistics using R $h [electronic resource] : $b quantitative tools for data analysis and data science / $c Daniel J. Denis.
250 $a 1st ed.
260 $a Hoboken, NJ : $b John Wiley & Sons, $c 2020.
300 $a 1 online resource (xvii, 366 p.) : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a Introduction to applied statistics -- Introduction to R and computational statistics -- Exploring data with R : essential graphics and visualization -- Means, correlations, counts : drawing inferences using easy-to-implement statistical tests -- Power analysis and sample size estimation using R -- Analysis of variance : fixed effects, random effects, mixed models and repeated measures -- Simple and multiple linear regression -- Logistic regression and the generalized linear model -- Multivariate analysis of variance (MANOVA) and discriminant analysis -- Principal components analysis -- Exploratory factor analysis -- Cluster analysis -- Nonparametric tests.
520 $a "This book provides a user-friendly and practical guide on R, with emphasis on covering a broader range of statistical methods than previous books on R. This is a "how to" book and will be of use to undergraduates and graduate students along with researchers and professionals who require a quick go-to source to help them perform essential statistical analyses and data management tasks in R. The book only assumes minimal prior knowledge of statistics, providing readers with the tools they need right now to help them understand and interpret their data analyses. This book covers univariate, bivariate, and multivariate statistical methods, as well as some nonparametric tests. It provides students with a hands-on easy-to-read manual on the wealth of applied statistics and essential R computing that they will need for their theses, dissertations, and research publications. A strength of this book is its scope of coverage of univariate through to multivariate procedures, while simultaneously serving as a friendly introduction to R software"-- $c Provided by publisher.
588 $a Description based on print version record.
650 0 $a R (Computer program language) $3 679069
650 0 $a Mathematical statistics $x Data processing $v Congresses. $3 675570 $3 731111
650 0 $a Multivariate analysis $v Problems, exercises, etc. $3 683933 $3 733644
650 0 $a Analysis of variance $v Textbooks. $3 1342735
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119549963