Understanding Applying Basic Statistical Methods Using R

Understanding & Applying Basic Statistical Methods Using R

Understanding and Applying Basic Statistical Methods Using R remarkably conquers any hindrance between propels in the measurable writing and methods routinely utilized by non-analysts. Giving a theoretical premise to understanding the relative benefits and uses of these methods, the book highlights current bits of knowledge and advances applicable to fundamental systems regarding managing non-ordinariness, exceptions, heteroscedasticity (unequal changes), and curvature. Including a manual for R, the book utilizes R programming to investigate starting factual ideas and standard methods for managing known issues related with exemplary procedures. Altogether classroom tried, the book incorporates segments that attention on either R programming or computational points of interest to enable the reader to wind up noticeably familiar with fundamental ideas and standards basic regarding understanding and applying the numerous methods as of now accessible.

Understanding and Applying Basic Statistical Methods Using R

Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox’ Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.

Understanding and Applying Basic Statistical Methods Using R