Visual Analytics - An Interaction of Sight and Thought - JMP

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Trends, patterns, and exceptions come to light. The presentation of data as text, such as you see in this table, is perfect when you need precise values or when the purpose is to look up or compare individual values, but not when you wish to see patterns, trends, and exceptions, or to make comparisons. When this is your goal, visualizations work best. When data is presented visually, it is given visible form, and from this we can easily glean insights that would take a long time to piece together from the same data presented textually, if ever. This graph of the same data that appears in the table makes brings to light several of the stories contained in the data that weren’t obvious before, and it did so instantly. When] we visualize the data effectively and suddenly, there is what Joseph Berkson called ‘interocular traumatic impact’: a conclusion that hits us between the eyes. (Visualizing Data, William S. Cleveland, Hobart Press, 1993, page 12) Modern data graphics can do much more than simply substitute for small statistical tables. At their best, graphics are instruments for reasoning about quantitative information. Often the most effective way to describe, explore, and summarize a set of numbers – even a very large set – is to look at pictures of those numbers. Furthermore, of all methods for analyzing and communicating statistical information, well-designed data graphics are usually the simplest and at the same time the most powerful. (The Visual Display of Quantitative Information, Edward R. Tufte, Graphics Press: Cheshire, CT 1983, Introduction)
A picture David is worth visits a thousand America. words. As we all know, the right picture can sometimes tell a story in a way that no amount of words could ever match. To take advantage of visualization’s great potential, we first must know when pictures rather than words are needed.
Page 2 and 3: Visual Analytics An Interaction of
Page 4 and 5: Hurray data! Hurray technology! We
Page 6 and 7: Upon this gifted age, in its dark h
Page 8 and 9: We must tap into that steady stream
Page 10 and 11: Data analysts JMP are now sexy. Dat
Page 12 and 13: To do this we need the right skills
Page 14 and 15: Two of the right skills • Statist
Page 16 and 17: What is visual thinking? Temple Gra
Page 18 and 19: We need greater balance. Modes of r
Page 20 and 21: Leonardo da Vinci For some four hun
Page 22 and 23: Complex problems require visual thi
Page 24 and 25: Tools extend our reach when they’
Page 26 and 27: Can computers replace us? Our brain
Page 28 and 29: Visualization empowers statistics.
Page 30 and 31: “I see!” There is an intimate c
Page 32 and 33: Vision is our dominant sense. 30% 7
Page 36 and 37: This visualization fails to do this
Page 38 and 39: The right balance 38 Information vi
Page 40 and 41: Many visualization tools feature de
Page 42 and 43: Bling your graph. Many software ven
Page 44 and 45: 3-D graphs are rarely useful. One o
Page 46 and 47: Even when there’s a 3 rd variable
Page 48 and 49: We don’t want to confuse people w
Page 50 and 51: Good visualizations and good visual
Page 52 and 53: This arrangement is even better yet
Page 54 and 55: Visual perception works according t
Page 56 and 57: Visual perception is not just camer
Page 58 and 59: Two essential activities • Multi-
Page 60 and 61: Data analysis requires rapid intera
Page 62 and 63: Key interactions of visual analysis
Page 64 and 65: Shneiderman’s Mantra “Overview
Page 66 and 67: Overview first, zoom and filter, th
Page 72 and 73: Attention is limited. Ever saw a ma
Page 74 and 75: Capacity = 3 or 4 chunks at a time
Page 76 and 77: Good analysis tools augment memory
Page 78 and 79: More dimensions through multiple vi
Page 80 and 81: Coordinated views expand what we ca
Page 82 and 83: Analytical challenges demand statis
Page 84 and 85:
Predictions rely on statistical mod
Page 86 and 87:
Finding and understanding the stori
Page 88 and 89:
Wisdom Knowledge Information Inform
Page 90 and 91:
O perpetual revolution of configure
Page 92 and 93:
Page 94 and 95:
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