Prescriptions for Working Statisticians (Springer Texts in Statistics) - hardcover

EAN (ISBN-13): 9780387966274
ISBN (ISBN-10): 0387966277
Hardcover
Publishing year: 1988
Publisher: Springer

Book in our database since 2015-03-13T05:44:55-04:00 (New York)
Detail page last modified on 2022-07-23T09:35:28-04:00 (New York)
ISBN/EAN: 9780387966274

ISBN - alternate spelling:
0-387-96627-7, 978-0-387-96627-4
Alternate spelling and related search-keywords:
Book title: springer texts

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Information from Publisher

Author: Albert Madansky
Title: Springer Texts in Statistics; Prescriptions for Working Statisticians
Publisher: Springer; Springer US
295 Pages
Publishing year: 1988-06-24
New York; NY; US
Weight: 0,610 kg
Language: English
85,55 € (DE)
87,95 € (AT)
106,60 CHF (CH)
Not available, publisher indicates OP

BB; Book; Hardcover, Softcover / Mathematik/Sonstiges; Angewandte Mathematik; Verstehen; statistics; Variance; analysis of variance; Boxplot; normal distribution; B; Applications of Mathematics; Mathematics and Statistics; BC; EA

0 A Thoughtful Student’s Retrospective on Statistics 101.- 0. Introduction.- 1. The Introductory Model.- 2. The Regression Model.- References.- 1 Testing for Normality.- 0. Introduction.- 1. Normal Plots.- 2. Regression Procedures.- (a) Shapiro—Wilk Statistic.- (b) Filliben Statistic.- (c) D’Agostino Statistic.- 3. Studentized Range.- 4. Moment Checking.- 5. Standard Tests of Goodness-of-Fit.- (a) Chi-Square Test.- (b) Kolmogorov Test.- (c) Durbin Test.- 6. Evaluation.- Appendix I.- References.- 2 Testing for Homoscedasticity.- 0. Introduction.- 1. Comparing Variances of Two Normal Distributions.- 2. Testing Homoscedasticity of Many Populations.- (a) Bartlett Test.- (b) Normal Score Procedure (Fligner—Killeen).- (c) Use of Analysis of Variance (Levene).- (d) Evaluation.- 3. Regression Residuals.- (a) Standard Estimates.- (b) Homoscedastic Estimated Residuals.- (i) BLUS.- (ii) Recursive Residuals.- 4. Testing Homoscedasticity of Regression Residuals.- (a) Goldfeld—Quandt Procedure.- (b) Lagrange Multiplier Test.- (c) White Procedure.- (d) Robust Procedures.- (e) Nonparametric Tests.- (f) Adapting Tests of Homogeneity of Variances.- (g) Evaluation.- Appendix I.- References.- 3 Testing for Independence of Observations.- 0. Introduction.- 1. Parametric Procedures.- (a) Independence of Observations.- (b) Autocorrelation.- (c) Independence of Regression Residuals.- (d) Box—Pierce Statistic.- 2. Nonparametric Procedures.- (a) Runs Above and Below the Median.- (b) Runs Up-and-Down.- (c) Rank von Neumann Ratio.- References.- 4 Identification of Outliers.- 0. Introduction.- 1. Normal Distribution.- (a) One Outlier.- (b) Multiple Outlier Indication.- (c) Multiple Outlier Detection—Known Number.- (d) Multiple Outlier Detection—Unknown Number.- 2. Nonparametric Procedures.- 3. Outliers in Regression.- References.- 5 Transformations.- 0. Introduction.- 1. Deflating Heteroscedastic Regressions.- 2. Variance Stabilizing Transformations.- 3. Power Transformations (Box—Cox).- (a) Maximum Likelihood.- (b) Hinkley Estimation Procedure.- (c) Graphic Procedure.- 4. Letter-Values and Boxplots.- 5. Power Transformations of Regression Independent Variables.- Appendix I.- References.- 6 Independent Variable Selection in Multiple Regression.- 0. Introduction.- 1. Criteria for Goodness of Regression Model.- 2. Stepwise Procedures.- (a) Order of Selection of Variables.- (b) Theoretical Description.- (c) Cutoff Rules.- (d) Example.- 3. Multicollinearity.- (a) Description of the Phenomenon.- (b) Diagnostics.- (c) Ridge Regression.- References.- 7 Categorical Variables in Regression.- 0. Introduction.- 1. Two Sample Tests.- (a) Parametric Procedures.- (b) Nonparametric Procedures.- 2. Analysis of Variance via Regression (Model I).- (a) One-Way Anova.- (b) Unbalanced Two-Way Anova with Only Main Effects.- (c) Unbalanced Two-Way Anova with Interaction.- (d) Median Polish.- 3. Components of Variance (Model II).- 4. Dichotomous Dependent Variables.- References.- 8 Analysis of Cross-Classified Data.- 0. Introduction.- 1. Independence in the r1 × r2 Table.- (a) General.- (b) 2 × 2 Tables.- 2. Log-Linear Models in the r1 × r2 Table.- 3. The Three-Dimensional Table.- 4. Analysis of Cross-Classifications with Ordered Categories.- 5. Latent Class Model.- Appendix I.- Appendix II.- References.- Index of Reference Tables.