Statistical Analysis and Data Display : An Intermediate Course with Examples in R 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. They emphasize how to construct and interpret graphs. They discuss principles of graphical design. They identify situations where visual impressions from graphs may need confirmation from traditional tabular results. All chapters have exercises. The authors provide and discuss R functions for all the new graphical display formats. All graphs and tabular output in the book were constructed using these functions. 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. In depth discussions of regression analysis analysis of variance and design of experiments are followed by introductions to analysis of discrete bivariate data nonparametrics logistic regression and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The Second Edition features graphs that are completely redrawn using the more powerful graphics infrastructure provided by Rs lattice package. There are new sections in several of the chapters revised sections in all chapters and several completely new appendices. New graphical material includes: • an expanded chapter on graphics; • a section on graphing Likert Scale Data to build on the importance of rating scales in fields from population studies to psychometrics; • a discussion on design of graphics that will work for readers with color deficient vision; • an expanded discussion on the design of multi panel graphics; • expanded and new sections in the discrete bivariate statistics chapter on the use of mosaic plots for contingency tables including the n×2×2 tables for which the Mantel Haenszel Cochran test is appropriate; • an interactive (using the shiny package) presentation of the graphics for the normal and t tables that is introduced early and used in many chapters. The new appendices include discussions of R the HH package designed for R (the material in t ...