The truthful art : data, charts, and maps for communication

No matter what your actual job title, you are--or soon will be--a data worker.

Every day, at work, home, and school, we are bombarded with vast amounts of free data collected and shared by everyone and everything from our co-workers to our calorie counters. In this highly anticipated follow-up to The Functional Art--Alberto Cairo's foundational guide to understanding information graphics and visualization--the respected data visualization professor explains in clear terms how to work with data, discover the stories hidden within, and share those stories with the world in the form of charts, maps, and infographics. In The Truthful Art, Cairo transforms elementary principles of data and scientific reasoning into tools that you can use in daily life to interpret data sets and extract stories from them.

The Truthful Art explains:

* The role infographics and data visualization play in our world

* Basic principles of data and scientific reasoning that anyone can master

* How to become a better critical thinker

* Step-by-step processes that will help you evaluate any data visualization (including your own)

* How to create and use effective charts, graphs, and data maps to explain data to any audience

The Truthful Art is also packed with inspirational and educational real-world examples of data visualizations from such leading publications as The New York Times, The Wall Street Journal, Estado de São Paulo (Brazil), Berliner Morgenpost (Germany), and many more.

• Preface p. xiii
• Introduction p. 1
• Part I Foundations
• 1 What We Talk About When We Talk About Visualization p. 27
• To Learn More p. 40
• 2 The Five Qualities of Great Visualizations p. 41
• The Hockey Stick Chart p. 43
• Truthful p. 45
• Functional p. 50
• Beautiful p. 53
• Insightful p. 59
• Enlightening p. 60
• To Learn More p. 65
• Part II Truthful
• 3 The Truth Continuum p. 69
• Dubious Models p. 71
• The Mind, That Clumsy Modeler p. 76
• Why Are We So Often Mistaken? p. 79
• Mind Bug 1: Patternicity p. 81
• Mind Bug 2: Storytelling p. 82
• Mind Bug 3: Confirmation p. 84
• Truth Is Neither Absolute, Nor Relative p. 86
• The Skills of the Educated Person p. 97
• To Learn More p. 97
• 4 Of Conjectures and Uncertainty p. 99
• The Scientific Stance p. 100
• From Curiosity to Conjectures p. 101
• Hypothesizing p. 105
• An Aside on Variables p. 105
• On Studies p. 107
• Doing Experiments p. 110
• About Uncertainty p. 112
• To Learn More p. 116
• Part III Functional
• 5 Basic Principles of Visualization p. 121
• Visually Encoding Data p. 123
• Choosing Graphic Forms p. 125
• A Grain of Salt p. 129
• Practical Tips About those Tricky Scales p. 135
• Organizing the Display p. 138
• Put Your Work to the Test p. 141
• To Learn More p. 148
• 6 Exploring Data with Simple Charts p. 151
• The Norm and the Exceptions p. 152
• The Mode, the Median, and the Mean p. 153
• Weighting Means p. 155
• Range p. 157
• Some Fun with Ranges p. 160
• To Learn More p. 166
• 7 Visualizing Distributions p. 167
• The Variance and the Standard Deviation p. 171
• Standard Deviation and Standard Scores p. 173
• Presenting Stories with Frequency Charts p. 178
• How Standardized Scores Mislead Us p. 183
• Peculiarities of the Normal Distribution p. 188
• Percentiles, Quartiles, and the Box Plot p. 191
• Manipulating Data p. 194
• Frequency Over Time p. 195
• To Learn More p. 197
• 8 Revealing Change p. 199
• Trend, Seasonality, and Noise p. 201
• Decomposing a Time Series p. 201
• Visualizing Indexes p. 210
• From Ratios to Logs p. 214
• How Time Series Charts Mislead p. 217
• Communicating Change p. 220
• To Learn More p. 231
• 9 Seeing Relationships p. 233
• From Association to Correlation p. 236
• Smoothers p. 240
• Matrices and Parallel Coordinate Plots p. 242
• Correlation for Communication p. 248
• Regression p. 257
• From Correlation to Causation p. 259
• Data Transformation p. 261
• To Learn More p. 262
• 10 Mapping Data p. 263
• Projection p. 265
• Data on Maps p. 271
• Point Data Maps p. 271
• Line Maps p. 277
• The Basics of Choropleth Maps p. 280
• Classifying Data p. 282
• Using Choropleth Maps p. 287
• Other Kinds of Data Maps p. 293
• To Learn More p. 296
• 11 Uncertainty and Significance p. 299
• Back to Distributions p. 302
• The Standard Error p. 305
• Building Confidence Intervals p. 308
• Disclosing Uncertainty p. 312
• The Best Advice You'll Ever Get: Ask p. 316
• How Has Stuff Been Measured? p. 317
• Dispatches from the Data Jungle p. 318
• Significance, Size, and Power p. 321
• To Learn More p. 325
• Part IV Practice
• 12 On Creativity and Innovation p. 329
• The Popularizers p. 334
• News Applications p. 338
• Those Enchanting Europeans p. 356
• Making Science Visual p. 360
• Culture Data p. 364
• The Artistic Fringes p. 367
• Epilogue p. 375
• Index p. 376