This book is organized into 3 general categories: the research process and how data that has been collected can be organized, presented and summarized (chapters 1 - 4); the process of conducting statistical analyses to test research questions, and hypotheses and issues and controversies regarding the process (chapters 5 - 10) and the last section which examines statistical procedures used in research situations that vary in the number of independent variables in the study, as well as how the independent and dependent variables have been measured (chapters 11 - 14). Every chapter contains learning checks which include review questions, and exercises are included at the end of every chapter to help assess what was learned.

Are you a researcher or instructor who has been wanting to learn R and RStudio (R), but you don't know where to begin? Do you want to be able to perform all the same functions you use in IBM (R) SPSS (R) in R? Is your license to IBM (R) SPSS (R) expiring, or are you looking to provide your students guidance to a freely-available statistical software program? Moving from IBM (R) SPSS (R) to R and RStudio (R): 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 (R) users just the information they need to transition their data analyses from SPSS to R.