Richard M. Heiberger - Böcker

R, a free and open source program, is one of the most powerful and the fastest-growing statistics program. Microsoft Excel is the most widely used spreadsheet program, but many statisticians consider its statistical tools too limited.In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language.Data can be transferred between R and Excel “the Excel way” by selecting worksheet ranges and using Excel menus. R’s basic statistical functions and selected advanced methods are available from an Excel menu. Results of the computations and statistical graphics can be returned back into Excel worksheet ranges. RExcel allows the use of Excel scroll bars and check boxes to create and animate R graphics as an interactive analysis tool.The book is designed as a computational supplement to introductory statistics texts and the authors provide RExcel examples covering the topics of the introductory course.

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data--showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying tabular listings—for all the methods they cover. Complete R scripts for all examples and figures are provided for readers to use as models for their own analyses.This book can serve as a standalone text for statistics majors at the master’s level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. Classical concepts and techniques are illustrated with a variety of case studies using both newer graphical tools and traditional tabular displays.New graphical material includes:an expanded chapter on graphicsa section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometricsa discussion on design of graphics that will work for readers with color-deficient visionan expanded discussion on the design of multi-panel graphicsexpanded and new sections in the discrete bivariate statistics capter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel–Haenszel–Cochran test is appropriatean interactive (using the shiny package) presentation of the graphics for the normal and t-tables that is introduced early and used in many chapters