Forecasting US Presidential Elections with Mixed Models

4.3
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Coursera Project Network
在此指导项目中,您将:

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中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
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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.

您要培养的技能

  • Forecasting
  • Election
  • Linear Regression
  • Statistical Models
  • Mixed Model

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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)

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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