Interactive Graphics for Data Analysis

Interactive Graphics for Data Analysis : Principles and Examples

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Interactive Graphics for Data Analysis: Principles and Examples discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets. Fundamentals of Interactive Statistical Graphics The first part of the book summarizes principles and methodology, demonstrating how the different graphical representations of variables of a dataset are effectively used in an interactive setting. The authors introduce the most important plots and their interactive controls. They also examine various types of data, relations between variables, and plot ensembles. Case Studies Illustrate the Principles The second section focuses on nine case studies. Each case study describes the background, lists the main goals of the analysis and the variables in the dataset, shows what further numerical procedures can add to the graphical analysis, and summarizes important findings. Wherever applicable, the authors also provide the numerical analysis for datasets found in Cox and Snell's landmark book. Understand How to Analyze Data through Graphical Means This full-color text shows that interactive graphical methods complement the traditional statistical toolbox to achieve more complete, easier to understand, and easier to interpret more

Product details

  • Hardback | 290 pages
  • 216 x 276 x 38mm | 1,406.13g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 186 black & white illustrations
  • 1584885947
  • 9781584885948
  • 1,439,723

Table of contents

Introduction PRINCIPLES Interactivity Queries Selection and Linked Highlighting Linking Analyses Interacting with Graphics Examining a Single Variable Categorical Data Continuous Data Transforming Data Weighted Plots Interactions between Two Variables Two Categorical Variables One Categorical Variable and One Continuous Variable Two Continuous Variables Multidimensional Plots Mosaic Plots Parallel Coordinate Plots Trellis Displays Plot Ensembles and Statistical Models Response Models ANOVA Loglinear Models Geographical Data More Interactivity Sorting and Ordering Zooming Multiple Views Interactive Graphics Dynamic Graphics Missing Values Large Data Unaffected, Summary-Based Plots Glyph-Based Plots EXAMPLES How to Pass an Exam Washing-What Makes the Difference The Influence of Smoking on Birthweight The Titanic Disaster Revisited Housing Rent Prices in Munich What Makes a Tour de France Winner How to Survive Thirty Years' War Classification of Italian Olive Oils E-Voting in the 2004 Florida Election Appendix: Mondrian Reference Quick Start Guide Plots Commands Reference Card References Authors Indexshow more

About Matthias Schonlau

Munich, Germany Madison, New Jersey, USA Rutgers University, New Brunswick, New Jersey, USA Carnegie Mellon University, Pennsylvania, USA Royal Holloway University of London, UK University of California, Irvine, California, USAshow more

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