Forecasting US Presidential Elections with Mixed Models

提供方
Coursera Project Network
在此指導項目中,您將:

Learn how the US elects Presidents in the Electoral College

Understand the basics of mixed effects models

Build a forecasting model to simulate the election using mixed effects models

Clock2 hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

ForecastingElectionLinear RegressionStatistical ModelsMixed Model

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Overview of Forecasting Elections (Lecture)

  2. Overview of How the US Elects Presidents (Lecture)

  3. Stylized Facts About Voting (Lecture)

  4. Types of Forecasting Models (Lecture)

  5. Building a Fundamentals Based Forecasting Model (Lecture)

  6. Setting Up the Dataset (Coding)

  7. Fitting the Model (Coding)

  8. Extracting Variances (Coding)

  9. Simulating Errors (Coding)

  10. Viewing the Winner (Coding)

指導項目工作原理

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