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Everything * you need to know about the psychology of perception to - - PowerPoint PPT Presentation

Everything * you need to know about the psychology of perception to make effective visualisations Hadley Wickham, Rice University Thursday, July 19, 12 Everything * you need to know about the psychology of perception to make


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Everything* you need to know about the psychology of perception† to make effective visualisations‡

Hadley Wickham, Rice University

Thursday, July 19, 12
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Everything* you need to know about the psychology of perception† to make effective visualisations‡

* that I can cram into 40 minutes

Hadley Wickham, Rice University

Thursday, July 19, 12
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Everything* you need to know about the psychology of perception† to make effective visualisations‡

* that I can cram into 40 minutes

† but I’m not a psychologist

Hadley Wickham, Rice University

Thursday, July 19, 12
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Everything* you need to know about the psychology of perception† to make effective visualisations‡

‡ in my opinion

* that I can cram into 40 minutes

† but I’m not a psychologist

Hadley Wickham, Rice University

Thursday, July 19, 12
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SLIDE 5 http://www.dreamsystemsmedia.com/blog/index.php/social-media-statistics-of-the-day/ Thursday, July 19, 12
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SLIDE 6

Match perceptual and data topology

1

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SLIDE 7

Which represents the larger value?

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SLIDE 8

Which represents the larger value?

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SLIDE 9

Which represents the larger value?

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SLIDE 10

Which represents the larger value?

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SLIDE 11

Which represents the larger value?

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SLIDE 12

Which represents the larger value?

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SLIDE 13

Which represents the larger value?

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SLIDE 14

Which represents the larger value?

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SLIDE 15

What are the three important components

  • f colour?
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SLIDE 16

RGB

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r g b

+50/255 R +50/255 G +50/255 B +100/255 R +100/255 G +100/255 B Thursday, July 19, 12
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RGB HSV HSL HCL

(aka polar LUV)

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hcl hsv hsl

http://en.wikipedia.org/wiki/HSV_color_space#Disadvantages Thursday, July 19, 12
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RGB HSV HSL HCL

(aka polar LUV)

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SLIDE 21

h c l

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SLIDE 22

chroma

luminance

hue

Munsell, Albert H. (1905). A Color Notation. Boston: G. H. Ellis Co. Thursday, July 19, 12
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Why care?

Perceptually uniform Hue is unordered. Use evenly spaced hues with equal chroma and luminance to make aesthetically pleasing discrete palettes. Chroma and luminance are ordered. Easy to make perceptually uniform gradients by varying either (or both). Never use rainbow scales again!

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Aesthetic Topology Position Ordered Size Ordered Luminance Ordered Chroma Ordered Shape Unordered Hue Unordered

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Make important comparisons easy

2

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SLIDE 26 a b
  • W. S. Cleveland and R. McGill. Graphical perception:

Theory, experimentation and application to the development of graphical methods. Journal of the American Statistical Association, 79 (387):531–554, 1984.

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SLIDE 27 a b Thursday, July 19, 12
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SLIDE 28 a b Thursday, July 19, 12
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SLIDE 29 a b Thursday, July 19, 12
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SLIDE 30 a b Thursday, July 19, 12
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SLIDE 31 Cleveland & McGill's Results 1.0 1.5 2.0 2.5 3.0 T1 T2 T3 T4 T5 Log Error Crowdsourced Results 1.0 1.5 2.0 2.5 3.0 T1 T2 T3 T4 T5 T6 T7 T8 T9
  • J. Heer and
  • M. Bostock.
Crowdsourcing graphical perception: Using mechanical turk to assess visualization design. In CHI 2010, 2010. Thursday, July 19, 12
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We perceive relative differences

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We perceive relative differences

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Position Length / Angle Area Volume / Chroma / Luminance Close objects are easier to compare than distant objects × × Perception is relative

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SLIDE 35 http://www.dreamsystemsmedia.com/blog/index.php/social-media-statistics-of-the-day/ Thursday, July 19, 12
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SLIDE 36 price count 1000 2000 3000 4000 5000 6000 1000 2000 3000 4000 5000 6000 Fair Premium 5000 10000 15000 Good Ideal 5000 10000 15000 Very Good 5000 10000 15000 Thursday, July 19, 12
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SLIDE 37 price density 0e+00 1e−04 2e−04 3e−04 4e−04 5e−04 5000 10000 15000 cut Fair Good Very Good Premium Ideal Thursday, July 19, 12
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Common misunderstanding Pie charts are bad! Die pie chart, DIE

Thursday, July 19, 12
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SLIDE 39

Common misunderstanding Pie charts are bad! Die pie chart, DIE Pie charts are bad when you want to accurately compare two numbers

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SLIDE 40

Common misunderstanding Pie charts are bad! Die pie chart, DIE Pie charts are bad when you want to accurately compare two numbers But: As good as bars for estimating percentage of whole. Better than bars for comparing compound proportions (A + B vs C + D)

Thursday, July 19, 12
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Common misunderstanding Pie charts are bad! Die pie chart, DIE Pie charts are bad when you want to accurately compare two numbers But: As good as bars for estimating percentage of whole. Better than bars for comparing compound proportions (A + B vs C + D)

  • I. Spence. No Humble Pie: The Origins and Usage of a

Statistical Chart. Journal of Educational and Behavioral Statistics, 30:353–368, 2005.

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SLIDE 42 x y1 0.2 0.4 0.6 0.8 1.0 2 4 6 8 10

Beware

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SLIDE 43

Beware

http://www.michaelbach.de/ot/sze_sineIllusion/index.html Thursday, July 19, 12
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SLIDE 44 http://www.michaelbach.de/ot/sze_sineIllusion/index.html

Beware

Thursday, July 19, 12
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SLIDE 45 http://www.michaelbach.de/ot/sze_sineIllusion/index.html

Beware

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SLIDE 46 http://www.michaelbach.de/ot/sze_sineIllusion/index.html

Beware

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Ensure important comparisons are close Use position, then length/area, then chroma/luminance If possible, display comparisons directly

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Visual connections should reflect real connections

3

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SLIDE 49 Thursday, July 19, 12
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SLIDE 50 Thursday, July 19, 12
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SLIDE 51 Thursday, July 19, 12
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SLIDE 52 Thursday, July 19, 12
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SLIDE 53 Thursday, July 19, 12
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SLIDE 54 Thursday, July 19, 12
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SLIDE 55 x y −0.5 0.0 0.5 1.0
  • −0.5
0.0 0.5 1.0 1.5

Beware

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SLIDE 56 x y −0.5 0.0 0.5 1.0
  • −0.5
0.0 0.5 1.0 1.5

Beware

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Beware of animation!

4

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Beware of animation!

4

(Compare in space, not time)

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SLIDE 59

We often miss gradual changes too We often don’t notice abrupt changes

http://youtu.be/FWSxSQsspiQ?t=0m12s http://youtu.be/1nL5ulsWMYc

And movement makes us miss other changes

http://visionlab.harvard.edu/silencing/ Thursday, July 19, 12
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SLIDE 60 http://www.nytimes.com/interactive/2009/07/31/business/20080801-metrics-graphic.html Thursday, July 19, 12
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Match perceptual and data topology

1

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Make important comparisons easy

2

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Visual connections should reflect real connections

3

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SLIDE 64

Beware of animation!

4

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Visualisation is only

  • ne part of data

analysis

5

*

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SLIDE 66

Transform Visualise Model

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SLIDE 67

Thanks!

Thursday, July 19, 12