Title of Research Output

The Data Science of Predicting Elections

Faculty

Political Science

Supervisor Name

Zack Taylor

Keywords

political science, psephology, opinion polls, election prediction, forecasting

Description

Psephology is the statistical study of election data, often used by data journalists and political operatives to predict the results of elections before they occur. In a Canadian context, this new field of data science has been notably used by CBC and Maclean's to create prediction models for federal and provincial elections.

This project created one such model to predict the 2022 Ontario General Election. It ran under the conventional Uniform Swing method with regional poll averages from CBC News used as inputs.

Acknowledgements

Thank you to Professor Zack Taylor, the Undergraduate Student Research Internship program, the Faculty of Political Science and the International Relations Program.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Document Type

Poster

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The Data Science of Predicting Elections

Psephology is the statistical study of election data, often used by data journalists and political operatives to predict the results of elections before they occur. In a Canadian context, this new field of data science has been notably used by CBC and Maclean's to create prediction models for federal and provincial elections.

This project created one such model to predict the 2022 Ontario General Election. It ran under the conventional Uniform Swing method with regional poll averages from CBC News used as inputs.

 

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