Book contents
- Polls, Pollsters, and Public Opinion
- Methodological Tools in the Social Sciences
- Polls, Pollsters, and Public Opinion
- Copyright page
- Contents
- Figures
- Graphs
- Quadrants
- Tables
- Acknowledgments
- 1 The Three-Hatted Pollster
- Part I The Fundamentals of Public Opinion
- Part II The Pollster as Data Scientist
- Part III The Pollster as Fortune Teller
- 8 Cognitive Biases in Prediction
- 9 Triangulating Election Prediction
- 10 Decision Inputs
- Part IV The Pollster as Spin Doctor
- Index
9 - Triangulating Election Prediction
from Part III - The Pollster as Fortune Teller
Published online by Cambridge University Press: 01 November 2024
- Polls, Pollsters, and Public Opinion
- Methodological Tools in the Social Sciences
- Polls, Pollsters, and Public Opinion
- Copyright page
- Contents
- Figures
- Graphs
- Quadrants
- Tables
- Acknowledgments
- 1 The Three-Hatted Pollster
- Part I The Fundamentals of Public Opinion
- Part II The Pollster as Data Scientist
- Part III The Pollster as Fortune Teller
- 8 Cognitive Biases in Prediction
- 9 Triangulating Election Prediction
- 10 Decision Inputs
- Part IV The Pollster as Spin Doctor
- Index
Summary
Forecasting elections is a high-risk, high-reward endeavor. Today’s polling rock star is tomorrow’s has-been. It is a high-pressure gig. Public opinion polls have been a staple of election forecasting for almost ninety years. But single source predictions are an imperfect means of forecasting, as we detailed in the preceding chapter. One of the most telling examples of this in recent years is the 2016 US presidential election. In this chapter, we will examine public opinion as an election forecast input. We organize election prediction into three broad buckets: (1) heuristics models, (2) poll-based models, and (3) fundamentals models.
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- Polls, Pollsters, and Public OpinionA Guide for Decision-Makers, pp. 126 - 146Publisher: Cambridge University PressPrint publication year: 2024