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020			_a9781071817001
040			_aIIITD
082	0	0	_a005.5 _bTOK-M
100	1		_aTokunaga, Howard
245	1	0	_aMoving from IBM SPSS to R and RStudio : _ba statistics companion _cby Howard T. Tokunaga
260			_aLos Angeles : _bSAGE, _c©2022
300			_axvi, 293 p. : _bcol. ill. ; _c23 cm.
505			_tChapter 1. Introduction to R _tChapter 2. Preparing to Use R and Rstudio _tChapter 3. R Terms, Concepts, and Command Structure _tChapter 4. Introduction to Rstudio _tChapter 5. Conducting Rstudio Sessions: A Detailed Example _tChapter 6. Conducting Rstudio Sessions: A Brief Example _tChapter 7. Conducting Statistical Analyses Using This Book: A Detailed Example _tChapter 8. Conducting Statistical Analyses Using This Book: A Brief Example _tChapter 9. Working With Data Frames and Variables in R _tChapter 10. Conducting Statistical Analyses Using SPSS Syntax
520			_a"Are you a researcher or instructor who has been wanting to learn R and RStudio®, but you don't know where to begin? Do you want to be able to perform all the same functions you use in IBM® SPSS® in R? Is your license to IBM® SPSS® expiring, or are you looking to provide your students guidance to a freely-available statistical software program? Moving from IBM® SPSS® to R and RStudio ®: A Statistics Companion is a concise and easy-to-read guide for users who want to know learn how to perform statistical calculations in R. Brief chapters start with a step-by-step introduction to R and RStudio, offering basic installation information and a summary of the differences. Subsequent chapters walk through differences between SPSS and R, in terms of data files, concepts, and structure. Detailed examples provide walk-throughs for different types of data conversions and transformations and their equivalent in R. Helpful and comprehensive appendices provide tables of each statistical transformation in R with its equivalent in SPSS and show what, if any, differences in assumptions factor to into each function. Statistical tests from t-tests to ANOVA through three-factor ANOVA and multiple regression and chi-square are covered in detail, showing each step in the process for both programs. By focusing just on R and eschewing detailed conversations about statistics, this brief guide gives adept SPSS users just the information they need to transition their data analyses from SPSS to R"--
630	0	0	_aSPSS (Computer file)
650		0	_aSocial sciences
650		0	_aR (Computer program language)
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942			_2ddc _cBK
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