Advanced Quantitative Methods:
Description and Prediction
Summer Math Camp

Conceptual mastery of statistical methods for public policy, focusing on application rather than mechanics

API 209 • Summer 2024
Prof: Dan Levy | Summer TF: Rony Rodriguez
Harvard University

Select Academic Term/Year:

Summer TF

Course details

  • Check schedule page
  • August 15-August 28, 2024
  • Time: Varies
  • Wexner 436. HKS

Contacting me

The best way to reach me is through email or Slack. I’ll do my best to respond as quickly as possible, but please understand if there’s a bit of a delay—sometimes things get busy! Looking forward to helping out with any questions you have.

📑 Course Overview

This summer camp focuses on advanced R programming, specifically on four key areas of data manipulation using the tidyverse. This is a continuation of the pre-summer assignment you completed, where you started using Posit Cloud. There is no formal syllabus for this course, as it is designed to be hands-on and interactive, emphasizing practical application over traditional lecture formats.

🎯 Learning Objectives

By the end of this summer camp, you will be able to:

  • Master Advanced Data Manipulation Techniques: Apply complex filtering, selection, and data reshaping operations using the tidyverse.
  • Create Elegant Data Visualizations: Utilize advanced ggplot2 features to produce publication-quality visuals and interactive plots.
  • Build and Interpret Statistical Models: Develop and diagnose statistical models, including regression and mixed models, to analyze real-world data.
  • Automate and Reproduce Research Workflows: Use RMarkdown and workflow automation tools to create reproducible, efficient research workflows.

Focus:

The course centers on applying advanced R programming concepts to solve practical data problems. Emphasis is placed on mastering the tidyverse, creating high-quality data visualizations, constructing robust statistical models, and automating research processes for efficiency and reproducibility.

How:

  • Hands-On Learning: The course is designed around interactive coding sessions where you’ll actively engage with datasets, applying techniques as you learn them.
  • Real-World Applications: Each lesson is tied to a real-world problem or dataset, ensuring that what you learn is immediately relevant and applicable.
  • Collaborative Projects: You will work on collaborative projects that simulate actual research scenarios, allowing you to practice and refine your skills in a team setting.
  • Feedback and Iteration: Regular feedback loops and peer reviews will help you iteratively improve your code and understanding, promoting deeper learning.

Throughout the camp, you will:

  • Discover how to solve complex data problems using advanced R techniques.
  • Distinguish between different methods for data manipulation and visualization, understanding when and why to use each.
  • Learn to automate repetitive tasks and create workflows that enhance the efficiency and reproducibility of your research.

This camp is about not just learning the concepts but mastering their application to become a better R programmer before the semester starts.