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Cutting Through The Noise: Tracking The Ups And Downs Of The 2004 Presidential Race Samuel S.-H. Wang Program in Neuroscience Princeton University.

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Presentation on theme: "Cutting Through The Noise: Tracking The Ups And Downs Of The 2004 Presidential Race Samuel S.-H. Wang Program in Neuroscience Princeton University."— Presentation transcript:

1 Cutting Through The Noise: Tracking The Ups And Downs Of The 2004 Presidential Race Samuel S.-H. Wang Program in Neuroscience Princeton University

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5 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

6 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

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8 http://election.princeton.edu

9 Went on line in July Over 1,000,000 hits 160,000 visitors on Nov. 1 and 2

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11 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

12 Race 2004, Real Clear Politics The explosion of state polls in 2004

13 Compretitive pressure discourages the sharing of polling data

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16 23 Battleground States

17 Simplicity Openness Acceptance of all data Frequent updating Principles of analysis for an Internet audience

18 The meta-analysis

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20 Andrea Moro

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22 Gallup national data 2004

23 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

24 Tracking the effects of news events

25 Estimating the value of an individual vote Application: deploying volunteer and advertising resources

26 Estimating the bias of the Electoral College Final national popular margin: Bush by 2.8%

27 The Electoral College Bias of 2004 2004 bias: 80 EV, 2%

28 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

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31 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions

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36 The Winter of (Post-Election) Discontent

37 Exit polls

38 County-level data in Florida

39 Were pre-election polls consistent with outcomes?

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42 I.election.princeton.edu II.Meta-analysis of polls III.Application to campaigns IV.Adjustments to polling data V.Learning from the outcome VI.Future directions Better time-averaging, media acceptance

43 Going back two weeks ago, your web site was probably the most convincing and objective web site on the proper way to analyze the Electoral College and president elections. Then all of a sudden during the last two weeks, your HOPE and WISHES for a Kerry victory clouded your otherwise solid/scientific/unbiased analysis….Professors at major IVY league colleges like Princeton have (perhaps unfairly) a double standard of utmost integrity and OBJECTIVITY in making assumptions, performing analysis, and in presenting their results to the community. The (obviously unfair) perception from the conservative right is the following. Why should I continue to support Princeton with financial contributions, when their extremely biased left-wing professors continue to teach their liberal political agenda (via their research and curriculum) to the young (and easily impressionable) college students?…In my opinion, your web site was the best one on the internet for predicting the 2004 president election (up until about 10/15). John Shumaker, November 3, 2004 The mail

44 Dear John, Your paragraph that professors must be objective is very thought-provoking. As a lab scientist I am continually testing ideas, some cherished. At the same time I have to be prepared when I am wrong, and I am often wrong. Normally these errors are corrected by factual evidence, at which point I revise my thinking. In this case I am in a public sphere, and my error is visible to many readers, including you. The reason that you, an astute reader, could detect this bias is that I documented everything. I provided data, code, explanations, and drew a bright line between data and assumptions. You did not find that on other sites, which is presumably why you read my site. In my view, total openness is an essential part of good critical reasoning. In my work and with students here, I am similarly open. I have found that the most thoughful ones respond as you have - if a problem exists, they call me on it. This is what you are doing. If you have doubts about elite universities, keep in mind that what you are asking for involves a dispassion that I don't have about anything, including this problem. In short, I admit to personal bias….However, that bias stemmed from interest in what would otherwise be a fairly dry estimation problem. I think nearly all your sources of information have some bias or another. Unlike many of those other sources, I put my biases where you can see them. Yours sincerely, Sam Wang November 3, 2004

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