CASt online resources R software Using R for introductory statistics by John Verzani (2005). Textbook presenting elementary concepts and methods with extensive R code examples. Includes univariate, bivariate and multivariate data, statistical distributions, simulations, confidence intervals, significance tests, goodness of fit, linear and nonlinear regression, ANOVA, and appendices of graphics, GUIs and programming in R. Statistics: An introduction using R by Michael J. Crawley (2005). Introductory statistics with strong focus on R code. Topics include variance, single and two samples, linear modeling, regression, ANOVA and ANCOVA, Poisson data, proportions, and censoring. Data analysis and graphics using R: An example-based approach by John Maindonald and John Braun (2003). Textbook seeking to provide tools for scientists performing statistical analyses. Topics include introduction to R, statistical distributions, formal inference, linear and multiple regression, smoothing, Poisson regression, ANOVA, time series, tree-based classification, multivariate exploration and discrimination. Modern applied statistics with S-PLUS by W. N. Venables and B. D. Ripley (4th ed, 2003). Well-respected textbook with extensive S (closely related to R) code, it discusses S programming and graphics, linear and nonlinear modeling, robust statistics, censoring, multivariate analysis, tree-based methods, time series and spatial point processes. Return to CASt bibliographies