Emil Hafeez is a Senior Data Analyst at NYU Langone’s Department of Population Health, where he leads complex analyses relating to health policy and health economics, including evaluating the impact of COVID-19 on health disparities among NYC schoolchildren and investigating the influence of food policies on large national sales datasets. He has experience in data engineering and analysis, program evaluation, and project management; his interests include using causal inference for identifying policy levers and effects. Emil has an MS in Biostatistics from Columbia University and an MSPH in International Health Systems from Johns Hopkins School of Public Health, as well as a BS from NYU.
R is a powerful open source language and environment for statistical computing and graphics. R provides a wide selection of statistical and graphical techniques. It is rapidly becoming the leading language in data science and statistics. R can easily tackle linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering and more.
This 7-week course leads the students into the R world, helps them master the basics and prepares them with plenty resources for self-advancement in the future. The course offers students basic programing knowledge and effective data analysis skills in R in the context of public policy-making and policy evaluation. Students will learn how to install R and RStudio, comprehend and use R data objects, become familiar with base R and several statistical and graphing packages. The course will also teach students to develop their own R functions, which they can use, improve or adapt in the future.