Methods Talk, January 21, 2011

8/7/2019 Methods Talk, January 21, 2011

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High Dimension Visualization

in Political Science:How to make beautiful data displays

David Sparks

Duke University


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Visualization: Three arbitrary categories

Infographics: Not what Im talking about Primarily factoids

Statistical Graphics: Make an argument Distilled representation of the results of analysis

Information Visualization: Show the data Often high-dimensional, large-N


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Infographics: Not what Im talking about Primarily factoids




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Factoids, not data

http://www.boston.com/bostonglobe/ideas/naps/


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Explanations, not data

http://www.dnapolicy.org/resources/Cloning_infographic_final.jpg


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Stereotypes, not data

http://www.informationisbeautiful.net/leftvright_world.html


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Stereotypes, not data

David McCandless and Stefanie Posavec


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Nothing new (1854)

http://bibliodyssey.blogspot.com


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PowerPoint as the enemy

The New York Times


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Framing

http://docs.house.gov/gopleader/House- Democrats-Health-Plan.pdf


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Infographics: Not what Im talking about Factoids




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Statistical Graphics

Gelman: Make use of familiar forms

Discovery of the unexpected

Graphics as alternative to tables and models

Distilled, reduced, minimized Make an argument

Dont mislead


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Very unnecessary graph, use a table

http://www.neuroscience.com/graphic.html


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One number, in text

USDoL via http://www.perceptualedge.com/blog/?p=266


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Why toroidal?

http://www.nevron.com/


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Superfluity

Edward Tuftes The Visual Display of Quantitative Information


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Misleading graphs

See: How to Lie With Statistics (Huff 1954)

Breaking from convention can be(intentionally) misleading


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Poor scaling

http://mediamatters.org/blog/201007010030


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Bad math

http://eagereyes.org/blog/2009/bri ng-out-your-dreadful-charts


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Good color

http://hdr.undp.org/en/reports/global/hdr2009/


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Good graphs:Model reporting


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Infographics: Not what Im talking about Factoids




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Information Visualization

Gelman: Creative, cutting-edge

Visual puzzles

Alternatives to photos and cartoons

High density oftennecessary for multipledimensions

Macro- and micro-level information

Showing data, not presenting results


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Network ties

Inherently multidimensional

n n Matrix of 0/1 for tie/no tie betweeneach pair ofnodes

Thus, data is n dimensional


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Making a point

arbitrarian.wordpress.com


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Macro impressions

miller-mccune.com


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Micro detail


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A story in multiple dimensions

Challenge: To illustrate an institutional history

through the movement of its agents

Subject:P

artisan

ship, geography an

d ideologyin the U.S. Senate

Solution: Timeline depicting breadth and detail


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Closer view


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Specific detail

url citation


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Same data, multiple representations

url citation


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Movement over time

url citation


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Different audience, different approach


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Different audience, different approach


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A history in multiple dimensions

Challenge: To illustrate political history and

dynamics through electoral results

Subject:P

artisan

ship, geography an

dtransformation inU.S. politics

Solution: Maps with a third dimension encodedin color


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Throwing away data


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Continuous choropleth


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Distortion to incorporate weight


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Three parties


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Isarithmic approach


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Small multiple time series


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Interpolated isarithmic

More fluid transitions http://www.youtube.com/watch?v=k4h62jRiUcc&fmt=22

Some issues: Map projection

Interpolation Color scheme

Does convey a lot of information, and does

appear to have made (some) people thin

k.

k d


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Making distinctions

To recap:

Statistical graphics Simple, familiar

Show conclusions, make an argument

Information visualization/Data display Deep, multi-level

Show data, allow exploration

What about high-dimensional statisticalgraphics?

bi i l i l d


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Combining multiple needs

132,480 simulations of Congressional voting

Depicting the effect of parameters on

estimates of ideological dimensionality

Parameters of interest: True dimensionality

Separation between party means

Ideological versus distributive motivations

Challenge: illustrate how a relationshipbetween two variables is influenced by other

variables

i 1


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Iteration 1

I i 2


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Iteration 2

I i 3


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Iteration 3

It ti 4


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Iteration 4

It ti 5


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Iteration 5

It ti 6 (Fi l)


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Iteration 6 (Final)

C l i


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Conclusions

Let ends determine means

Dont be misleading

Think about conventions

Make the viewers job easy

C l i


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Conclusions


Dont be misleading



Concl sions


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Conclusions


Dont be misleading



Conclusions


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Conclusions


Dont be misleading



Conclusions


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Conclusions


Dont be misleading



Where to go from here?


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Where to go from here?

Think about the rhetoric of graphics

Google Edward Tufte, Hadley Wickham

Visit www.duke.edu/~cdd11/tex.html

Interested in tutorial session?

Any questions?


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Any questions?

Thanks

[email protected]/site/dsparks

Documents

Methods Talk, January 21, 2011