The course is intended for graduate students in all fields. Advanced undergraduate students are welcome.
This course introduces the basics of data analysis and statistical computing with an emphasis on applications in social science. You will learn a variety of research methods as well as how to conduct empirical research. More specifically, you will learn:
1. how to find, collect and transform data for your analysis
2. how to analyze the data and report the result of your analysis
3. how to manage and record your project
A typical class session combines a 45-minute lecture and 45-minute hands-on computer session. Students must bring their own laptop to class.
The topics we plan to cover in class include:
● Introduction to R and Rstudio
● Introduction to Programing with R
● Visualizing Data
● Introduction to Web Scraping
● Linear Regression
● Instrumental Variables
● Regression Discontinuity Design
● Generalized Linear Regression
● Experiments and Matching Methods
● Network Data
● Texts as Data
● Student Presentations
There are no required books for the class. The reading list will be distributed in the first session. We usually read a chapter from various textbooks and an article.