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R data analysis without programming

Record Type:	Language materials, printed : Monograph/item
Title/Author:	R data analysis without programming/ David W. Gerbing.
Author:	Gerbing, David W.
Published:	New York :Routledge, : 2014.,
Description:	xvi, 291 p. :ill. :
Subject:	R (Computer program language) -
Online resource:	Click here to view
ISBN:	9781315856759 (e-book : PDF)

R data analysis without programming
Gerbing, David W.

R data analysis without programming[electronic resource] /David W. Gerbing. - New York :Routledge,2014. - xvi, 291 p. :ill.

Includes bibliographical references and index.

ch. 1. R for data analysis -- ch. 2. Read/write data -- ch. 3. Edit data -- ch. 4. Categorical variables -- ch. 5. Continuous variables -- ch. 6. Means, compare two samples -- ch. 7. Compare multiple samples -- ch. 8. Correlation -- ch. 9. Regression I -- ch. 10. Regression II -- ch. 11. Factor/item analysis.

"This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without programming. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights of the book include:Quick Starts that introduce readers to the concepts and commands reviewed in the chapters. Margin notes that highlight, define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output.Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate how to interpret results. Two data sets, provided on the website and analyzed multiple times in the book, provide continuity throughout. End of chapter worked problems help readers test their understanding of the concepts. A website that features the lessR program, the book's data sets referenced in standard text and SPSS formats so readers can practice using R/lessRby working through the text examples and worked problems, PDF slides for each chapter, solutions to the book's worked problems, links to R/lessR videos to help readers better understand the program, and more. An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used, taught in departments of psychology, business, education, and other social and health sciences, this book is also appreciated by researchers interested in using R for their data analysis. Prerequisites include basic statistical knowledge. Knowledge of R is not assumed"--

Mode of access: World Wide Web.

ISBN: 9781315856759 (e-book : PDF)Subjects--Topical Terms:

679069
R (Computer program language)
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA276.45.R3 / G46 2014

Dewey Class. No.: 519.502855133 / G363

R data analysis without programming
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245 1 0 $a R data analysis without programming $h [electronic resource] / $c David W. Gerbing.
260 $a New York : $b Routledge, $c 2014.
300 $a xvi, 291 p. : $b ill.
504 $a Includes bibliographical references and index.
505 0 $a ch. 1. R for data analysis -- ch. 2. Read/write data -- ch. 3. Edit data -- ch. 4. Categorical variables -- ch. 5. Continuous variables -- ch. 6. Means, compare two samples -- ch. 7. Compare multiple samples -- ch. 8. Correlation -- ch. 9. Regression I -- ch. 10. Regression II -- ch. 11. Factor/item analysis.
520 $a "This book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without programming. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights of the book include:Quick Starts that introduce readers to the concepts and commands reviewed in the chapters. Margin notes that highlight, define, illustrate, and cross-reference the key concepts. When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output.Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate how to interpret results. Two data sets, provided on the website and analyzed multiple times in the book, provide continuity throughout. End of chapter worked problems help readers test their understanding of the concepts. A website that features the lessR program, the book's data sets referenced in standard text and SPSS formats so readers can practice using R/lessRby working through the text examples and worked problems, PDF slides for each chapter, solutions to the book's worked problems, links to R/lessR videos to help readers better understand the program, and more. An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used, taught in departments of psychology, business, education, and other social and health sciences, this book is also appreciated by researchers interested in using R for their data analysis. Prerequisites include basic statistical knowledge. Knowledge of R is not assumed"-- $c Provided by publisher.
530 $a Also available in print edition.
538 $a Mode of access: World Wide Web.
650 0 $a R (Computer program language) $3 679069
650 0 $a Mathematical statistics $x Data processing. $3 558446
655 7 $a Electronic books. $2 local $3 554714
776 1 $z 9780415641739 (hardback) $z 9780415657204 (paperback)
856 4 0 $u http://www.tandfebooks.com/isbn/9781315856759 $z Click here to view