'Small Data' Enabled Prediction Of Obama's Win, Say Economists.
The article examines how economists used computer programming to predict the results of the 2012 U.S. presidential election, which was won by U.S. President Barack Obama. Justin Wolfers of the University of Michigan describes several forecasting methods that were used which incorporate data such as...
| Publicado en: | Communications of the ACM Vol. 56; no. 5; pp. 23 - 26 |
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| Formato: | Artículo |
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Association for Computing Machinery
May2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=87500037&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 87500037 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: May2013 vid: 56 iid: 5 pid: 68 pub: Association for Computing Machinery artinfo: ui: 87500037 10.1145/2447976.2447984 ppf: 23 ppct: 3 formats: tig: atl: 'Small Data' Enabled Prediction Of Obama's Win, Say Economists. aug: au: Hyman, Paul su: Election forecasting United States presidential election, 2012 Economists Big data Regression analysis Obama, Barack, 1961- Wolfers, Justin United States sug: subj: United States Election forecasting United States presidential election, 2012 Economists Big data Regression analysis Obama, Barack, 1961- Wolfers, Justin ab: The article examines how economists used computer programming to predict the results of the 2012 U.S. presidential election, which was won by U.S. President Barack Obama. Justin Wolfers of the University of Michigan describes several forecasting methods that were used which incorporate data such as gross domestic product (GDP) growth, public opinion polls, and stock market prices. Particular attention is given to the lack of using big data, a term used for large information sets. Patrick Hummel, a research scientist at Internet corporation Google, describes how he used simple linear regression to predict the election. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2013 holdings: @attributes: islocal: N |
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