1. Why Did Clinton Lose? Why Did Trump Win?
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014
Why Did Clinton Lose? Why Did Trump Win?
Milo Schield
Augsburg College
Editor:
US Rep: International Statistical Literacy Project
TC Metro Critical Thinking Club
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 1 1

2. We Want Explanations: Wrong Color Pantsuits?
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 2
We Want Explanations: Wrong Color Pantsuits? .
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 2 2

3. Plausible Explanations Must be Supported by Data
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 3
Plausible Explanations Must be Supported by Data .
2008SchieldNNN6up.pdf
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4. FBI Comey Letters . 2nd 1st 4 Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 4
FBI Comey Letters .
2nd
1st
2014-Schield-ICOTS-6up
2008SchieldNNN6up.pdf 4 4

5. What if only ____ voted? Women vs. Men
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 5
What if only ____ voted? Women vs. Men
Source:
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 5 5

6. What If Only ___ Voted? People of Color vs. White
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 6
What If Only ___ Voted? People of Color vs. White .
2008SchieldNNN6up.pdf
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7. What If Only ____ Voted? Whites: Women vs Men
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 7
What If Only ____ Voted? Whites: Women vs Men .
2008SchieldNNN6up.pdf
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8. What if only ____ Voted? Whites: College vs. No College
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 8
What if only ____ Voted? Whites: College vs. No College .
Data Source: Nate Sliver (538) in mid October, 2016.
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 8 8

9. Exit Polls: Poll actual voters
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 9
Exit Polls: Poll actual voters .
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 9 9

10. Exit Polls Voters Asked on Exit
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 10
Exit Polls Voters Asked on Exit
PLUS:
Best way to contact actual voters.
Connect candidate choice with multiple groups.
No undecided after voting
Get smaller subgroups.
MINUS:
Not necessarily representative. Sampling bias?
Some chose “None of the options” or “No answer”
Subject bias is still relevant.
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 10 10

11. Exit Poll Results: Questions with Two-Answers
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 11
Exit Poll Results: Questions with Two-Answers
What groups should each candidate focus on?
Pro-Clinton Groups (Most are for Clinton):
Sort by Group’s share of population
Sort by Clinton’s share of group vote
Source of Exit Poll Data:
2008SchieldNNN6up.pdf
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12. Pro-Hillary Exit-Poll Sheet Left Side
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 12
Pro-Hillary Exit-Poll Sheet Left Side
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 12 12

13. Pro-Hillary Exit-Poll Sheet Right Side
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 13
Pro-Hillary Exit-Poll Sheet Right Side
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 13 13

14. Multi-Group Choice-Based
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 14
Multi-Group Choice-Based
2008SchieldNNN6up.pdf
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15. Multi-Group Opinion-Based
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 15
Multi-Group Opinion-Based
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 15 15

16. Multi-Group Choice or Opinion-Based
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 16
Multi-Group Choice or Opinion-Based
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 16 16

17. Multi-Group: Fixed Conditions
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 17
Multi-Group: Fixed Conditions
2008SchieldNNN6up.pdf
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18. Critical Thinking Review What Other Data Would Help?
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 18
Critical Thinking Review What Other Data Would Help?
We have lots of data comparing Clinton & Trump.
Two-answer data (See Handout)
Multiple-answer data (3-7 choices)
Is this data sufficient/adequate for our decision? If not, what other data would be helpful?
We need time-data: Hillary compared to Obama. It takes a change to explain a change.
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 18 18

19. Time-Compare by Gender: Increase among Men
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 19
Time-Compare by Gender: Increase among Men .
20 point gender gap
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 19 19

20. Time-Compare by Race: Trump bested Romney in All
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 20
Time-Compare by Race: Trump bested Romney in All .
50 point race gap
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 20 20

21. Time-Compare by Income: Trump better in Low-Income
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 21
Time-Compare by Income: Trump better in Low-Income .
15 point income gap
Confounded by race
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 21 21

22. Time-Compare Among Whites by Education
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 22
Time-Compare Among Whites by Education .
30 point education gap:
After controlling for race
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 22 22

23. Biggest Problem: Confounding
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 23
Biggest Problem: Confounding
50 point gap by Race (70% White vs. 30% Non-White)
20 point gap by Gender (48% Men vs. 52% Women)
15 point gap by Income (Low vs High: Low is less than $50K)
5 point gap by Education (50% no College vs. 50% College)
Statistical Literacy: Take into account most important factors first.
Otherwise the results will be “confounded”. Simplest way: Selection!
30 point gap by Education among Whites (no College vs. College)
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 23 23

24. Women: White, High School or Less
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 24
Women: White, High School or Less .
14 pt gap
Control for Race and Education by Selection
Source: PEW Research Center
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 24 24

25. Men: White, High School or Less
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 25
Men: White, High School or Less .
38 pt gap
Control for Race and Education by Selection
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 25 25

26. Psychological Explanation: Trump is a Populist
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 26
Psychological Explanation: Trump is a Populist .
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 26 26

27. Psychological Differences: Trump=Populist; Clinton=Not
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 27
Psychological Differences: Trump=Populist; Clinton=Not
Source. Oliver and Rahn (2016). Rise of Trumpenvolk: Populism in the 2016 Election. Annals AAPSS 667, Sept URL:
Trump
Clinton
Sanders
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 27 27

28. Critical Thinking Summary
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 28
Critical Thinking Summary
What kind of data do we need?
“It takes a change to explain a change” Time-based data is essential
If data doesn’t include the motivating reason or condition, that data will not be helpful.
Let’s look at some psychological “data”.
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 28 28

29. “Trumpland” Excerpt by Michael Moore
Schield ICOTS
Analyzing Numbers in the News
15 May 2008
2014 29
“Trumpland” Excerpt by Michael Moore
Uploaded Oct million views as of 12/03
Why
Trump
will win
2008SchieldNNN6up.pdf
2014-Schield-ICOTS-6up 29 29

30. Michael Moore “Trump’s election is going to be the biggest
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 30
Michael Moore
“On Nov 8, the dispossessed will walk into the voting booth and … vote … for the man that has threatened to upend and overturn the very system that has ruined their lives: Donald J. Trump”
“Trump’s election is going to be the biggest
‘fuck you’ ever recorded in human history”
“And it will feel good !!!”
2008SchieldNNN6up.pdf
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31. Why did Moore Get it Right?
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 31
Why did Moore Get it Right?
He had a personal relationship with the respondents.
Moore: “I know a lot of people in Michigan that are planning to vote for Trump and they don't necessarily agree with him. They're not racist or redneck, they're actually pretty decent people. After talking to a number of them, I wanted to write this.
“We went to union halls and guys that I grew up with — people who normally vote Democrat who are thinking of voting for Trump. That is a huge chunk of the population, especially where I'm from.”
2008SchieldNNN6up.pdf
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32. Critical Thinking Summary
Analyzing Numbers in the News
Schield ICOTS
15 May 2008
2014 32
Critical Thinking Summary
CTC1: Election poll forecasts -- closer to fortune telling
CTC2: Why Clinton Lost.
Looking at the wrong data can be debilitating!
It takes a change to explain a change ‘Movie’ data is better than ‘snapshot’ data
Take into account (control for) the biggest factor first
Simplest way to control for something: Selection
2008SchieldNNN6up.pdf
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