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Applied univariate, bivariate, and multivariate statistics = understanding statistics for social and natural scientists, with applications in SPSS and R /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applied univariate, bivariate, and multivariate statistics/ Daniel J. Denis.
其他題名:	understanding statistics for social and natural scientists, with applications in SPSS and R /
作者:	Denis, Daniel J.,
出版者:	Hoboken, NJ :John Wiley & Sons, : 2021.,
面頁冊數:	1 online resource.
附註:	Includes index.
標題:	Analysis of variance - Textbooks. -
電子資源:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119583004
ISBN:	9781119583004

Applied univariate, bivariate, and multivariate statistics = understanding statistics for social and natural scientists, with applications in SPSS and R /
Denis, Daniel J.,1974-

Applied univariate, bivariate, and multivariate statisticsunderstanding statistics for social and natural scientists, with applications in SPSS and R /[electronic resource] :Daniel J. Denis. - 2nd ed. - Hoboken, NJ :John Wiley & Sons,2021. - 1 online resource.

Includes index.

Preliminary considerations -- Introductory statistics -- Analysis of variance : fixed effects models -- Factorial analysis of variance : modeling interactions -- Introduction to random effects and mixed models -- Randomized blocks and repeated measures -- Linear regression -- Multiple linear regression -- Interactions in multiple linear regression : dichotomous, polytomous, and continuous moderators -- Logistic regression and the generalized linear model -- Multivariate analysis of variance -- Discriminant analysis -- Principal components analysis -- Factor analysis -- Path analysis and structural equation modeling.

"This second edition improves greatly on the first edition by making the book more accessible to a wider audience, through minimizing theoretical or technical jargon and maximizing conceptual understanding with easy applied software examples. As a book for applied social science, only the absolute necessary mathematics are used in motivating conceptual development and applications. This allows researchers and their students to apply these methods quickly, efficiently, and with relative ease without having to wade through dense technical arguments. Assuming only minimal prior exposure to statistics, by completion the reader will have a solid intuitive grasp of introductory univariate to relatively advanced multivariate statistical methods and be able to apply them efficiently and effectively using software. This revised edition has been thoroughly vetted to correct errata found in the first edition, is more concise and easy to use, and will lend itself well for a textbook in applied courses at both the senior undergraduate and beginning graduate levels. The book will also serve as a useful reference for practitioners and researchers in the aforementioned fields"--

ISBN: 9781119583004Subjects--Topical Terms:

1342735
Analysis of variance
--Textbooks.

LC Class. No.: QA279 / .D46 2021

Dewey Class. No.: 519.5/3

Applied univariate, bivariate, and multivariate statistics = understanding statistics for social and natural scientists, with applications in SPSS and R /
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100 1 $a Denis, Daniel J., $d 1974- $3 1342734
245 1 0 $a Applied univariate, bivariate, and multivariate statistics $h [electronic resource] : $b understanding statistics for social and natural scientists, with applications in SPSS and R / $c Daniel J. Denis.
250 $a 2nd ed.
260 $a Hoboken, NJ : $b John Wiley & Sons, $c 2021.
300 $a 1 online resource.
500 $a Includes index.
505 0 $a Preliminary considerations -- Introductory statistics -- Analysis of variance : fixed effects models -- Factorial analysis of variance : modeling interactions -- Introduction to random effects and mixed models -- Randomized blocks and repeated measures -- Linear regression -- Multiple linear regression -- Interactions in multiple linear regression : dichotomous, polytomous, and continuous moderators -- Logistic regression and the generalized linear model -- Multivariate analysis of variance -- Discriminant analysis -- Principal components analysis -- Factor analysis -- Path analysis and structural equation modeling.
520 $a "This second edition improves greatly on the first edition by making the book more accessible to a wider audience, through minimizing theoretical or technical jargon and maximizing conceptual understanding with easy applied software examples. As a book for applied social science, only the absolute necessary mathematics are used in motivating conceptual development and applications. This allows researchers and their students to apply these methods quickly, efficiently, and with relative ease without having to wade through dense technical arguments. Assuming only minimal prior exposure to statistics, by completion the reader will have a solid intuitive grasp of introductory univariate to relatively advanced multivariate statistical methods and be able to apply them efficiently and effectively using software. This revised edition has been thoroughly vetted to correct errata found in the first edition, is more concise and easy to use, and will lend itself well for a textbook in applied courses at both the senior undergraduate and beginning graduate levels. The book will also serve as a useful reference for practitioners and researchers in the aforementioned fields"-- $c Provided by publisher.
588 $a Description based on print version record.
650 0 $a Analysis of variance $v Textbooks. $3 1342735
650 0 $a Multivariate analysis $v Problems, exercises, etc. $3 683933 $3 733644
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119583004