Statistical Analysis and Data Display

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 RegressionMore Than One Predictor. - 10 Multiple RegressionDummy Variables and Contrasts. - 11 Multiple RegressionRegression Diagnostics. - 12 Two-Way Analysis of Variance. - 13 Design of ExperimentsFactorial Designs. - 14 Design of ExperimentsComplex Designs. - 15 Bivariate StatisticsDiscrete 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. 2Requirements 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 FactorizationCholesky. - 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. Language: English