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Data visualization — why, what and how
The document discusses data visualization, emphasizing its importance, practical applications, and theoretical foundations. It references various authors and methodologies, including principles from Stephen C. Few and Jean-Luc Doumont, and delves into visual perception and cognitive processes related to interpreting data. Additionally, it highlights the significance of clarity and truthfulness in presenting data.
Data visualization — why, what and how
- 1. Boris Gorelik, Ph.D. boris@gorelik.net http://data.blog Datavisualization — why, what and how?
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- 6. Boris Gorelik, Ph.D. boris@gorelik.net http://data.blog WooCommerce,Jetpack, Simplenote, Longreads, VaultPress, Akismet, Gravatar, Polldaddy, Cloudup Past Present
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- 9. From "Show methe numbers” by Stephen C. Few & From “Trees, Maps & Theorems” By Jean-luc Doumont
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- 14. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 15. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 16. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 17. Division/Department Headcount G&A Finance 15 Purchasing5 Information Systems 17 Sales Field Sales 47 Sales Operations 10 Engineering Product Development 22 Product Marketing 5 From “Trees, Maps & Theorems” By Jean-luc Doumont
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- 24. 70% 30% From "Show methe numbers” by Stephen C. Few
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- 32. Science? Art? Matter oftaste?
- 35. Stimulus Sensory Organ EyeEyeEye Brain PerceptualOrgan Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process)
- 36. Stimulus Sensory Organ EyeEyeEye Brain PerceptualOrgan Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) Preattentive attributes
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- 38. From "Show methe numbers” by Stephen C. Few
- 39. From "Show methe numbers” by Stephen C. Few
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- 41. From "Show methe numbers” by Stephen C. Few
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- 47. Stimulus Sensory Organ EyeEyeEye Brain PerceptualOrgan Iconic Memory Working Memory Long-term Memory Sensation (Physical Process) Perception (Cognitive Process) Preattentive attributes
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- 51. Truth, all truth,and nothing but the truth
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- 55. Data, enough data,and mostly data
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- 58. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 59. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 60. From “Trees, Maps& Theorems” By Jean-luc Doumont
- 61. line vs. dots colorlinewidth From “Trees, Maps & Theorems” By Jean-luc Doumont
- 62. Information channels line vs.dots colorline width From “Trees, Maps & Theorems” By Jean-luc Doumont
- 63. Information redundancy line vs.dots colorline width From “Trees, Maps & Theorems” By Jean-luc Doumont
- 64. Useful redundancy line vs.dots colorline width From “Trees, Maps & Theorems” By Jean-luc Doumont
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- 67. Gestalt principles Interplay betweenthe parts and the whole
- 68. Kurt Koffka (1886– 1941) The whole is “other” than the sum of its parts
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- 74. Proximity graph area text body datalabel event remark
- 75. Proximity graph area text body datalabel event remark
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- 78. Continuity 0 10,000 1 2 34 5 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Salaries (U.S. $) Female vs. Male Salary Distributions Pay Grades 110,000 0 10,000 1 2 3 4 5 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000 Salaries (U.S. $) Male vs. Female Salary Distributions Pay Grades 110,000 From "Show me the numbers” by Stephen C. Few
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- 80. Science? Art? Matter oftaste?
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