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The Half-Life of a Social Statistician Andrew Gelman 15 Nov 2012 Andrew Gelman The Half-Life of a Social Statistician
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The Half-Life of a Social Statistician

Andrew Gelman

15 Nov 2012

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

control

treatment

"before" measurement, x

"afte

r" m

easu

rem

ent,

y

Andrew Gelman The Half-Life of a Social Statistician

Estimated partisan bias in previous election

Est

imat

ed p

artis

an b

ias

(adj

uste

d fo

r st

ate)

-0.05 0.0 0.05

-0.0

50.

00.

05

no redistricting

bipartisan redistrict

Dem. redistrict

Rep. redistrict.

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ox

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x

•• •

•••

(favors Democrats)

(favors Republicans)

Andrew Gelman The Half-Life of a Social Statistician

grade

corr

elat

ion

1 2 3 4

0.8

0.9

1.0

controls

treated

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

From Wikipedia:

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Hierarchy of stories:

1. Joke, or fiction such as Harry Potter

2. Urban legend

3. Dubious story (the lost soldiers in the Alps)

4. Plausible but undocumented story (e.g., Iraqs weapons ofmass destruction)

5. Documented anecdote

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Andrew Gelman The Half-Life of a Social Statistician

Some reasons to believe:

I Mathematical theory (e.g., asymptotic convergence)

I Computer simulations (e.g., approximate coverage of intervals)

I Solutions to toy problems (e.g., 8 schools)

I Improved performance on benchmark problems

I Cross-validation and external validation

I Success as recognized in a field of application

I Success in the marketplace

Andrew Gelman The Half-Life of a Social Statistician


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