Introduction to R

R is a statistical software environment that is available, free of charge, from the Comprehensive R Archive Network (https://www.r-project.org). It is often used for database management, which includes such tasks as merging datasets, creating new variables, recoding variables, subsetting data, etc. It also contains a wide array of statistical routines found in commercial software packages, including (but certainly not limited to) Ordinary Least Squares (OLS), binary responses (Logit/Probit), Panel Data Econometrics, Two-stage Least Squares/Instrumental Variable, Linear and Generalized Linear Mixed-Effects Models, Quantile Regression, etc. This session will give an overview of the use of R for database management and statistical analysis. It will begin with reading/cleaning data, followed by commands for descriptive statistics and regression analysis. All are welcome.

Biography:

Adrian Rohit Dass is a Research Coordinator at the Institute of Health Policy, Management, and Evaluation at the University of Toronto. He holds a Masters Degree in Economics from the University of Guelph. He is interested in the application of econometric methods to survey and administrative data from longitudinal studies. His primary area of research is applied microeconometrics in the field of health economics.