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Summer R Bootcamp

Welcome

 

 

Welcome to Summer R Bootcamp. This website contains comprehensive notes and tutorials on topics covered in the bootcamp.

 

Objectives: Summer R Bootcamp is designed to equip our current/incoming students with a solid foundation in R, one of the most powerful and versatile programming languages in the data science community.

It aims to help current/incoming students gain an understanding of core concepts of R programming, give them experience with statistical procedures, and improve their coding skills in order to successfully complete the MA program curriculum.

Over the course of four weeks, you will dive into the essentials of R, from basic programming concepts to advanced data analysis techniques. You will be exposed to various topics of R programming through lecture notes, examples, and exercises. Those who successfully complete the summer bootcamp will be able to

  • Manipulate and wrangle data with different structures.
  • Develop skills to clean, manipulate, and analyze data.
  • Explore data via visualization and basic modeling for exploratory data analysis (EDA).
  • Tackle familiar statistical concepts.
  • Communicate results.

 

Timeline: July 8 – August 2 (4 weeks)

 

Below are topics covered in the Summer R Bootcamp:

Week 1: Base R

  • Data Types
  • Data Structures
  • Conditional Statements (Control Structures) & Loops
  • Functions

Week 2: Functional Programming and Tidyverse packages

  • Functional Programming
  • Dplyr Package
  • Tidyr Package

Week 3: Data Visualization, Communication, and Reporting Tools

  • Data Visualization (Base R and ggplot2 package)
  • Rmarkdown Files

Week 4: Basic Applied Statistics and Probability

  • Generating Probability Distributions and Random Samples
  • Statistical Inference
  • Linear Regression Models

 

Assignments: There will be no requirement to complete/submit homework assignments. Every week you will have a chance to complete self-assessment assignments (Problem Sets), which will NOT be graded (Solutions to these assignments will be provided).

In addition, you will be supported by teaching assistants (TAs), who will address your questions and walk you through tutorials and assignments (if needed) during the help room hours.