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This book is ideal for graduate and undergraduate courses in statistics beyond the introductory course, research methods, and/or any data analysis course, taught in departments of psychology, business, education, and other social and health sciences; this book is also appreciated by researchers doing data analysis. Prerequisites include basic statistical knowledge, though the concepts are explained from the beginning in the book. Previous knowledge of R is not assumed.
The new edition of this innovative book, R Data Analysis without Programming, prepares readers to quickly analyze data and interpret statistical results using R. Professor Gerbing has developed lessR, a ground-breaking method for alleviating the challenges of R programming. The lessR package extends R, removing the need for programming. This edition expands upon the first edition’s introduction to R through lessR, which enables the readers to learn how to organize data for analysis, read the data into R, and generate output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables with simple function calls. The text reviews and explains basic statistical procedures with the lessR enhancements added to the standard R environment. Using lessR, data analysis with R becomes immediately accessible to the novice user and easier to use for the experienced user.Highlights along with content new to this edition include:• Explanation and Interpretation of all data analysis techniques.
• Clear, relaxed writing style more effectively communicates the underlying concepts than more stilted academic writing.• Numerous examples of output from psychology, business, education, and other social sciences.• Two data sets are analyzed multiple times in the book, providing continuity throughout.• Integration with machine learning as regression analysis is presented from both the traditional perspective and from the

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