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Univariate, bivariate, and multivariate statistics using R[electronic resource] :quantitative tools for data analysis and data science /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	519.5/302855133
書名/作者:	Univariate, bivariate, and multivariate statistics using R : quantitative tools for data analysis and data science // Daniel J. Denis.
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:	Analysis of variance
標題:	Multivariate analysis
標題:	Mathematical statistics - Congresses. - Data processing
標題:	R (Computer program language)
ISBN:	9781119549963
ISBN:	9781119549918
ISBN:	9781119549956
書目註:	Includes bibliographical references and index.
內容註:	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.
摘要、提要註:	"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"--
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119549963

Univariate, bivariate, and multivariate statistics using R[electronic resource] :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:

136196
Analysis of variance

LC Class. No.: QA279 / .D45776 2020

Dewey Class. No.: 519.5/302855133

Univariate, bivariate, and multivariate statistics using R[electronic resource] :quantitative tools for data analysis and data science /
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020 $a 9781119549963 $q (electronic bk.)
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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 747974
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 Analysis of variance $3 136196
650 0 $a Multivariate analysis $3 136191
650 0 $a Mathematical statistics $x Data processing $v Congresses. $3 467910
650 0 $a R (Computer program language) $3 465792
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119549963