Introduction to Data Analytics and Policy

3 Credits.

This course introduces students to the fundamentals of statistical analysis as well as the R programming language. Students will learn the building blocks of descriptive and causal inference, including summary statistics, survey sampling, measurement, hypothesis testing, linear regression and probability theory. Students will also learn how to create data visualizations in R, including time series plots, scatter plots and bar graphs. In addition, students will focus on interpreting statistical ?ndings and presenting results in a compelling manner. By the end of the course, students will be able to conduct a statistical analysis to answer a meaningful policy question and will be prepared to take more advanced methods courses. Prerequisites: None.