ABOUT THIS COURSE
This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights.
The course first introduces a framework for thinking about the various purposes of statistical analysis. We’ll talk about how analysts use data for descriptive, causal and predictive inference. We’ll then cover how to develop a research study for causal analysis, compute and interpret descriptive statistics and design effective visualizations. The course will help you to become a thoughtful and critical consumer of analytics.
If you are in a field that increasingly relies on data-driven decision making, but you feel unequipped to interpret and evaluate data, this course will help you develop these fundamental tools of data literacy.
Difficulty Level: BEGINNER
Estimated Learning Time: 11 hours
SKILLS YOU WILL GAIN:
Probability & Statistics
Research and Design
Jennifer Bachner, PhD
Data Analytics and Policy Program