Welcome to R Review Course!

Instructor

Course details

  • August 19–August 23, 2024
  • 1:00–4:00 pm
  • 135B Ruttan
  • Syllabus (PDF)

Course Description

This is a one-week course designed as an introduction to R statistical software for incoming graduate students. R is the leading software used in Ph.D.-level econometric classes in APEC (APEC 8211-8214). For example, we extensively use R to conduct Monte Carlo simulations to understand the properties of different estimators and inference methods. In this course, we will go through the basics of R programming. Although the topics we can cover within five days are limited, I selected essential topics that would be directly helpful to establish a solid foundation for students’ R skills. These skills will not only be beneficial for first-year Ph.D. Econometrics classes but also for your personal research, empowering you to conduct independent studies and contribute to the field.


Learning Objectives

By completing the course, students will be able to

  • create an R project and know how to access and save data.
  • handle different types of base R objects (e.g. list, vector, matrix, and data.frame).
  • use basic data wrangling skills with the data.table package (e.g. subset rows, select and compute on columns, rename columns, perform aggregations by group, merge multiple datasets, and reshape wide-to-long and long-to-wide, respectively).
  • use basic ggplot functions to visualize data
  • write their own R functions.
  • write code for simple Monte Carlo Simulations with loop.

In preparation for the course

  • Download and Install R and R studio on your laptop. To do this, follow the procedure described in this website
  • Get UCard access to Ruttan Hall:
    • Request access to the building (Ruttan Hall)
  • Finish the Survey.
  • Bring your laptop to the class.

Lecture Style

Each lecture will be divided into three sessions, where each session consists of a 50-minute lecture and a 10-minute break.

By just looking at code, you cannot acquire the skills for coding. The only way to learn coding is to do it yourself! At the end of each topic, we will work on small quizzes to check your understanding level. In addition, there will be exercise problems at the end of the slides. These exercise problems require you to combine multiple operations you learned in the lecture. Of course, I do not expect you to solve the quizzes and exercise problems immediately. I want you to go through the problems many times until you feel comfortable. The solutions are included in the slides.

More about R coding

If you are interested in learning more about R programming, I recommend that you take APEC 8221 (001) Programming for Econometrics (7 week course, 2 credits). You can still register!