Avoiding Data Pitfalls
Avoiding Data Pitfalls
How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations
Jones, Ben
John Wiley & Sons Inc
12/2019
272
Mole
Inglês
9781119278160
15 a 20 dias
560
Chapter 1 The Seven Types of Data Pitfalls 1
Seven Types of Data Pitfalls 3
Pitfall 1: Epistemic Errors: How We Think About Data 3
Pitfall 2: Technical Traps: How We Process Data 4
Pitfall 3: Mathematical Miscues: How We Calculate Data 4
Pitfall 4: Statistical Slipups: How We Compare Data 5
Pitfall 5: Analytical Aberrations: How We Analyze Data 5
Pitfall 6: Graphical Gaffes: How We Visualize Data 6
Pitfall 7: Design Dangers: How We Dress up Data 6
Avoiding the Seven Pitfalls 7
"I've Fallen and I Can't Get Up" 8
Chapter 2 Pitfall 1: Epistemic Errors 11
How We Think About Data 11
Pitfall 1A: The Data-Reality Gap 12
Pitfall 1B: All Too Human Data 24
Pitfall 1C: Inconsistent Ratings 32
Pitfall 1D: The Black Swan Pitfall 39
Pitfall 1E: Falsifiability and the God Pitfall 43
Avoiding the Swan Pitfall and the God Pitfall 44
Chapter 3 Pitfall 2: Technical Trespasses 47
How We Process Data 47
Pitfall 2A: The Dirty Data Pitfall 48
Pitfall 2B: Bad Blends and Joins 67
Chapter 4 Pitfall 3: Mathematical Miscues 74
How We Calculate Data 74
Pitfall 3A: Aggravating Aggregations 75
Pitfall 3B: Missing Values 83
Pitfall 3C: Tripping on Totals 88
Pitfall 3D: Preposterous Percents 93
Pitfall 3E: Unmatching Units 102
Chapter 5 Pitfall 4: Statistical Slipups 107
How We Compare Data 107
Pitfall 4A: Descriptive Debacles 109
Pitfall 4B: Inferential Infernos 131
Pitfall 4C: Slippery Sampling 136
Pitfall 4D: Insensitivity to Sample Size 142
Chapter 6 Pitfall 5: Analytical Aberrations 148
How We Analyze Data 148
Pitfall 5A: The Intuition/Analysis False Dichotomy 149
Pitfall 5B: Exuberant Extrapolations 157
Pitfall 5C: Ill-Advised Interpolations 163
Pitfall 5D: Funky Forecasts 166
Pitfall 5E: Moronic Measures 168
Chapter 7 Pitfall 6: Graphical Gaffes 173
How We Visualize Data 173
Pitfall 6A: Challenging Charts 175
Pitfall 6B: Data Dogmatism 202
Pitfall 6C: The Optimize/Satisfice False Dichotomy 207
Chapter 8 Pitfall 7: Design Dangers 212
How We Dress up Data 212
Pitfall 7A: Confusing Colors 214
Pitfall 7B: Omitted Opportunities 222
Pitfall 7C: Usability Uh-Ohs 227
Chapter 9 Conclusion 237
Avoiding Data Pitfalls Checklist 241
The Pitfall of the Unheard Voice 243
Index 247
Chapter 1 The Seven Types of Data Pitfalls 1
Seven Types of Data Pitfalls 3
Pitfall 1: Epistemic Errors: How We Think About Data 3
Pitfall 2: Technical Traps: How We Process Data 4
Pitfall 3: Mathematical Miscues: How We Calculate Data 4
Pitfall 4: Statistical Slipups: How We Compare Data 5
Pitfall 5: Analytical Aberrations: How We Analyze Data 5
Pitfall 6: Graphical Gaffes: How We Visualize Data 6
Pitfall 7: Design Dangers: How We Dress up Data 6
Avoiding the Seven Pitfalls 7
"I've Fallen and I Can't Get Up" 8
Chapter 2 Pitfall 1: Epistemic Errors 11
How We Think About Data 11
Pitfall 1A: The Data-Reality Gap 12
Pitfall 1B: All Too Human Data 24
Pitfall 1C: Inconsistent Ratings 32
Pitfall 1D: The Black Swan Pitfall 39
Pitfall 1E: Falsifiability and the God Pitfall 43
Avoiding the Swan Pitfall and the God Pitfall 44
Chapter 3 Pitfall 2: Technical Trespasses 47
How We Process Data 47
Pitfall 2A: The Dirty Data Pitfall 48
Pitfall 2B: Bad Blends and Joins 67
Chapter 4 Pitfall 3: Mathematical Miscues 74
How We Calculate Data 74
Pitfall 3A: Aggravating Aggregations 75
Pitfall 3B: Missing Values 83
Pitfall 3C: Tripping on Totals 88
Pitfall 3D: Preposterous Percents 93
Pitfall 3E: Unmatching Units 102
Chapter 5 Pitfall 4: Statistical Slipups 107
How We Compare Data 107
Pitfall 4A: Descriptive Debacles 109
Pitfall 4B: Inferential Infernos 131
Pitfall 4C: Slippery Sampling 136
Pitfall 4D: Insensitivity to Sample Size 142
Chapter 6 Pitfall 5: Analytical Aberrations 148
How We Analyze Data 148
Pitfall 5A: The Intuition/Analysis False Dichotomy 149
Pitfall 5B: Exuberant Extrapolations 157
Pitfall 5C: Ill-Advised Interpolations 163
Pitfall 5D: Funky Forecasts 166
Pitfall 5E: Moronic Measures 168
Chapter 7 Pitfall 6: Graphical Gaffes 173
How We Visualize Data 173
Pitfall 6A: Challenging Charts 175
Pitfall 6B: Data Dogmatism 202
Pitfall 6C: The Optimize/Satisfice False Dichotomy 207
Chapter 8 Pitfall 7: Design Dangers 212
How We Dress up Data 212
Pitfall 7A: Confusing Colors 214
Pitfall 7B: Omitted Opportunities 222
Pitfall 7C: Usability Uh-Ohs 227
Chapter 9 Conclusion 237
Avoiding Data Pitfalls Checklist 241
The Pitfall of the Unheard Voice 243
Index 247