TY  - BOOK
AU  -  Chambers, John M.
AU  - Cleveland, William S.
AU  - Kleiner, Beat
AU  - Tukey, Paul A.
TI  - Graphical methods for data analysis
SN  - 9781315893204
U1  - 001.422 
PY  - 2018///
CY  - Boca Raton
PB  -  FL : CRC Press
KW  - Statistics -- Graphic methods -- Congresses.
KW  -  REFERENCE -- Questions & Answers.
KW  -  Computer graphics -- Congresses.
N1  -  	Cover; Title Page; Copyright Page; Preface; Contents; 1: Introduction; 1.1: Why Graphics?; 1.2: What is a Graphical Method for Analyzing Data?; 1.3: A Summary of the Contents; 1.4: The Selection and Presentation of Materials; 1.5: Data Sets; 1.6: Quality of Graphical Displays; 1.7: How Should This Book Be Used?; 2: Portraying the Distribution of a Set of Data; 2.1: Introduction; 2.2: Quantile Plots; 2.3: Symmetry; 2.4: One-Dimensional Scatter Plots; 2.5: Box Plots; 2.6: Histograms; 2.7: Stem-and-Leaf Diagrams; 2.8: Symmetry Plots and Transformations; 2.9: Density Traces. 2.10: Summary and Discussion2.11: Further Reading; Exercises; 3: Comparing Data Distributions; 3.1: Introduction; 3.2: Empirical Quantile-Quantile Plots; 3.3: Collections of Single-Data-Set Displays; 3.4: Notched Box Plots; 3.5: Multiple Density Traces; 3.6: Plotting Ratios and Differences; 3.7: Summary and Discussion; 3.8: Further Reading; Exercises; 4: Studying Two-Dimensional Data; 4.1: Introduction; 4.2: Numerical Summaries are not Enough; 4.3: Examples; 4.4: Looking at the Scatter Plots; 4.5: Studying the Dependence of y on x by Summaries in Vertical Strips. 4.6: Studying the Dependence of y on x by Smoothing4.7: Studying the Dependence of the Spread of y on x by Smoothing Absolute Values of Residuals; 4.8: Fighting Repeated Values with Jitter and Sunflowers; 4.9: Showing Counts with Cellulation and Sunflowers; 4.10: Two-Dimensional Local Densities and Sharpening; 4.11: Mathematical Details of Lowess; 4.12: Summary and Discussion; 4.13: Further Reading; Exercises; 5: Plotting Multivariate Data; 5.1: Introduction; 5.2: One-Dimensional and Two-Dimensional Views; 5.3: Plotting Three Dimensions at Once; 5.4: Plotting Four and More Dimensions. 5.5: Combinations of Basic Methods5.6: First Aid and Transformation; 5.7: Coding Schemes for Plotting Symbols; 5.8: Summary and Discussion; 5.9: Further Reading; Exercises; 6 Assessing Distributional Assumptions About Data; 6.1: Introduction; 6.2: Theoretical Quantile-Quantile Plots; 6.3: More on Empirical Quantiles and Theoretical Quantiles; 6.4: Properties of the Theoretical Quantile-Quantile Plot; 6.5: Deviations from Straight-Line Patterns; 6.6: Two Cautions for Interpreting Theoretical Quantile-Quantile Plots; 6.7: Distributions with Unknown Shape Parameters. 6.8: Constructing Quantile-Quantile Plots6.9: Adding Variability Information to a Quantile-Quantile Plot; 6.10: Censored and Grouped Data; 6.11: Summary and Discussion; 6.12: Further Reading; Exercises; 7: Developing and Assessing Regression Models; 7.1: Introduction; 7.2: The Linear Model; 7.3: Simple Regression; 7.4: Preliminary Plots; 7.5: Plots During Regression Fitting; 7.6: Plots After the Model is Fitted; 7.7: A Case Study; 7.8: Some Special Regression Situations; 7.9: Summary and Discussion; 7.10: Further Reading; Exercises; 8: General Principles and Techniques; 8.1: Introduction
N2  - "This book present graphical methods for analysing data. Some methods are new and some are old, some require a computer and others only paper and pencil; but they are all powerful data analysis tools. In many situations, a set of data? even a large set- can be adequately analyses through graphical methods alone. In most other situations, a few well-chosen graphical displays can significantly enhance numerical statistical analyses."--Provided by publish
ER  -