LEADER 05454nam 2200673Ia 450 001 9910144693603321 005 20170810195501.0 010 $a1-282-30777-0 010 $a9786612307775 010 $a0-470-31683-7 010 $a0-470-31766-3 035 $a(CKB)1000000000687564 035 $a(EBL)468776 035 $a(SSID)ssj0000337968 035 $a(PQKBManifestationID)11929337 035 $a(PQKBTitleCode)TC0000337968 035 $a(PQKBWorkID)10294368 035 $a(PQKB)11052668 035 $a(MiAaPQ)EBC468776 035 $a(PPN)159341159 035 $a(OCoLC)264615249 035 $a(EXLCZ)991000000000687564 100 $a19910207d1991 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aFundamentals of exploratory analysis of variance$b[electronic resource] /$fedited by David C. Hoaglin, Frederick Mosteller, John W. Tukey 210 $aNew York $cWiley$dc1991 215 $a1 online resource (456 p.) 225 0 $aWiley series in probability and mathematical statistics. Applied probability and statistics 300 $aDescription based upon print version of record. 311 $a0-471-52735-1 320 $aIncludes bibliographical references and index. 327 $aFundamentals of Exploratory Analysis of Variance; Contents; 1. Concepts and Examples in Analysis of Variance; 1A. Interaction in ANOVA; 1B. A Graphical Analysis of a Complex Experiment on the Hardness of Dental Gold; 1C. An Election Example; 1D. Why Main Effects and Interactions?; Exercises; 2. Purposes of Analyzing Data that Come in a Form Inviting Us to Apply Tools from the Analysis of Variance; 2A. Purposes Can Be Both Diverse and Unfamiliar; 2B. A Quantitative Microcosm; 2C. More Classic Purposes; 2D. Causation, Experimentation, and Observation; 2E. Summary; Exercises 327 $a3. Preliminary Examination of Data3A. Editing; 3B. Appreciating the Data; 3C. Plots of the Data; 3D. Boxplots; 3E. Stem-and-Leaf Displays; 4. Types of Factors and Their Structural Layouts; 4A. Types of Factors; 4B. Relationships Between Factors; 4C. One-way and Two-way Layouts; 4D. Three-Way and More-Way Layouts; 4E. Summary; Exercises; 5. Value-Splitting: Taking the Data Apart; 5A. Forming Overlays; 5B. Overlays for One-way Data; 5C. What the Residuals Tell Us; 5D. Comparing Overlays: An ANOVA Table; 5E. Designs with Two Crossed Factors; 5F. Interaction and Replication 327 $a5G. Two-Factor Designs with Replication5H. Two-Factor Data with Nesting; 5I. Other Descriptions; 5J. Summary; Exercises; 6. Value Splitting Involving More Factors; 6A. Three Crossed Factors; 6B. Four Crossed Factors; 6C. Latin Square Designs; 6D. Summary; Exercises; 7. Mean Squares, F Tests, and Estimates of Variance; 7A. Formal Inferences: The F Test; 7B. Broadening the Base for the F Test; 7C. (Optional) Note on the Relation of the Pitman-Welch Work to an Ordinary F Distribution; 7D. Confidence Intervals for u2 Under Ideal Conditions; 7E. Sensitivity to the Assumption of Normality 327 $aExercises8. Graphical Display as an Aid to Analysis; 8A. An Overview of Graphical Methods for One-way ANOVA; 8B. Graphical Display for Two-Factor Data; 8C. A Side-by-Side Plot Attuned to Mean Squares; 8D. A Detailed Example: Percentage of Americans Who Have Never Married; 8E. Patterns or Noise?; 8F. Exploring Residuals Graphically; 8G. Summary; Exercises; 9. Components of Variance; 9A. Structures Leading to Components in One-way Analysis of Variance; 9B. Example: Variance Components for Blood Pressure; 9C. Alternative Methods for Estimating Variance Components 327 $a9D. Confidence Intervals for Variance Components9E. Unbalanced Cases ( Expected-Mean-Square Method); 9F. Two-way Tables; 9G. Example: Nationalization of Electoral Forces; 9H. Summary; Exercises; 10. Which Denominator?; 10A. Analyzing the Structure; 10B. The Sampling or Pigeonhole Model; 10C. The Notion of "Above"; 10D. Three-Way Special Cases; 10E. Constructing an Appropriate Error Term; 10F. Estimation of Variance Components in a Two-way Analysis of Variance by Equating Average Values; 10G. An Alternative Model for Interaction in Two-way Analysis of Variance 327 $a10H. A Three-Way Example: Tumor Size 330 $aThe analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions. 410 0$aWiley Series in Probability and Statistics 606 $aAnalysis of variance 606 $aMathematical statistics 615 0$aAnalysis of variance. 615 0$aMathematical statistics. 676 $a519.5 676 $a519.538 701 $aHoaglin$b David C$g(David Caster),$f1944-$0101864 701 $aMosteller$b Frederick$f1916-2006.$045482 701 $aTukey$b John W$g(John Wilder),$f1915-2000.$0101780 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910144693603321 996 $aFundamentals of exploratory analysis of variance$92171213 997 $aUNINA