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Forecasting US Presidential Elections with Mixed Models
In this project-based course, you will learn how to forecast US Presidential Elections. We will use mixed effects models in the R programming language to build a forecasting model for the 2020 election. The project will review how the US selects Presidents in the Electoral College, stylized facts about voting trends, the basics of mixed effects models, and how to use them in forecasting.
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Rating | Not enough ratings |
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Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 3 (39 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Vinod Bakthavachalam |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming Mathematics |
Tags | Data Science Machine Learning Probability And Statistics |
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Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 3 (39 weeks ago) |
Cost | $9 |
From | Coursera Project Network via Coursera |
Instructor | Vinod Bakthavachalam |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Programming Mathematics |
Tags | Data Science Machine Learning Probability And Statistics |
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