1 Introduction and Motivation.- 2 Data and Statistics.- 3 Statistics Concepts.- 4 Graphs.- 5 Introductory Inference.- 6 One-Way Analysis of Variance.- 7 Multiple Comparisons.- 8 Linear Regression by Least Squares.- 9 Multiple Regression-More Than One Predictor.- 10 Multiple Regression-Dummy Variables and Contrasts.- 11 Multiple Regression-Regression Diagnostics.- 12 Two-Way Analysis of Variance.- 13 Design of Experiments-Factorial Designs.- 14 Design of Experiments-Complex Designs.- 15 Bivariate Statistics-Discrete Data.- 16 Nonparametrics.- 17 Logistic Regression.- 18 Time Series Analysis.- A Software.- A.1 Statistical Software.- A.2 Text Editing Software.- A.2.1 Emacs.- A.2.2 Microsoft Word.- A.3 Word Processing Software.- A.3.2 Microsoft Word.- A.4 Graphics Display Software.- A.5 Operating Systems.- A.6 Mathematical Fonts.- A.7 Directory Structure.- A.7.1 HOME Directory.- A.7.2 HH Book Online Files.- B.1 Create Your Working Directory and Make the HH Library Available.- B.1.3 Windows and R.- B.1.6 Unix and R.- B.4 HH Library Functions.- B.5 Learning the S Language.- B.6 S Language Style.- C SAS.- C.1 Make the HH Library Available.- C.1.1 Windows.- C.1.2 Unix.- C.2 Using SAS with HH.- C.2.1 Reading HH Datasets.- C.2.2 Any Other Data Files.- C.2.3 ASCII Data Files with TAB Characters.- C.2.4 Windows and Unix EOL (End-of-Line) Conventions.- C.3 Macros.- C.4 Learning the SAS Language.- C.5 SAS Coding Conventions.- D Probability Distributions.- D.1.1 An Example Involving Calculations with the Binomial Distribution.- D.2 Noncentral Probability Distributions.- E Editors.- E.1 Working Style.- E.2 Typography.- E.3 Emacs and ESS.- E.3.1 ESS.- E.3.2 Mouse and Keyboard.- E.3.3 Learning Emacs.- E.3.4 Requirements.- E.4 Microsoft Word.- E.4.1 Learning Word.- E.4.2 Requirements 6.- E.5 Microsoft Excel.- E.5.1 Database Management.- E.5.2 Organizing Calculations.- E.5.3 Excel as a Statistical Calculator.- E.6 Exhortations, Some of Which Are Writing Style.- E.6.1 Writing Style.- E.6.2 Programming Style and Common Errors.- E.6.3 Presentation of Results.- F Mathematics Preliminaries.- F.1 Algebra Review.- F.2 Elementary Differential Calculus.- F.3 An Application of Differential Calculus.- F.4 Topics in Matrix Algebra.- F.4.1 Elementary Operations.- F.4.2 Linear Independence.- F.4.3 Rank.- F.4.4 Quadratic Forms.- F.4.5 Orthogonal Transformations.- F.4.6 Orthogonal Basis.- F.4.8 Matrix Factorization-Cholesky.- F.4.9 Orthogonal Polynomials.- F.4.10 Projection Matrices.- F.4.11 Geometry ot Mlatrices.- F.4.12 Eigenvalues and Eigenvectors.- F.4.13 Singular Value Decomposition.- F.4.14 Generalized Inverse.- F.4.15 Solving Linear Equations.- F.5 Combinations and Permutations.- F.5.1 Factorial.- F.5.2 Permutations.- F.5.3 Combinations.- F.6 Exercises.- G Graphs Based on Cartesian Products.- G.1 Structured Sets of Graphs.- G.1.1 Cartesian Products.- G.1.2 Trellis Paradigm.- G.2 Scatterplot Matrices: splom and xysplom.- G.3 Cartesian Products of Sets of Functions.- G.4 Graphs Requiring Multiple Calls to xysplom.- G.5 Asymmetric Roles for the Row and Column Sets.- G.6 Rotated Plots.- G.7 Squared Residual Plots.- G.8 Alternate Presentations.- References.- List of Datasets.

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.