Forecasting US Presidential Elections with Mixed Models

4.3
estrellas
10 calificaciones
ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

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
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

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.

Habilidades que desarrollarás

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

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  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)

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Preguntas Frecuentes

Preguntas Frecuentes

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