02645nam a22002057a 4500003000600000005001700006008004100023020001800064040001000082082001700092100002100109245009200130260003300222300003900255505055800294520150800852630002502360650002002385650003402405IIITD20240501185923.0240501b |||||||| |||| 00| 0 eng d a9781071817001 aIIITD00a005.5bTOK-M1 aTokunaga, Howard10aMoving from IBM SPSS to R and RStudio :ba statistics companion cby Howard T. Tokunaga aLos Angeles :bSAGE,c©2022 axvi, 293 p. :bcol. ill. ;c23 cm. tChapter 1. Introduction to RtChapter 2. Preparing to Use R and RstudiotChapter 3. R Terms, Concepts, and Command StructuretChapter 4. Introduction to RstudiotChapter 5. Conducting Rstudio Sessions: A Detailed ExampletChapter 6. Conducting Rstudio Sessions: A Brief ExampletChapter 7. Conducting Statistical Analyses Using This Book: A Detailed ExampletChapter 8. Conducting Statistical Analyses Using This Book: A Brief ExampletChapter 9. Working With Data Frames and Variables in RtChapter 10. Conducting Statistical Analyses Using SPSS Syntax 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"--00aSPSS (Computer file) 0aSocial sciences 0aR (Computer program language)