Andrew Young School of Policy Studies, Georgia State University



If you learn how to look at data in the right way, you can explain riddles that otherwise might have seemed impossible —Dubner & Levitt, 2014

How dangerous is the new corona virus? Is a new treatment effective? Does gun ownership make you safer? What career to choose? Which schools provide better education? Do genetically modified foods create health risks? What cars are more reliable and less costly to own? Do cell phones contribute to auto accidents? Is global warming real?

Every day, scientists, policymakers, business strategists, and citizens face countless questions and need to make important decisions. How can we answer those questions? How should we act? The way we approach such questions determine the quality of the decisions we make and our ability to solve the problems we face.

Oftentimes, we make decisions based on intuition, convenient assumptions, anecdotal claims, or beliefs. But beliefs are not always backed by evidence and often misleading. Data, on the other hand, are a more reliable ground for decision making. Data analysis helps us understand complex situations and make informed decisions.

I am Yuriy Davydenko, and this course is about the process of reasoning and learning from data. It is the introduction to the art and science of extracting insights from data using graphs and numerical summaries. It focuses on statistical analysis methods applicable to the study of policy and management. In this course, you will learn how to ask the right questions, produce data that can answer those questions, analyze data, and draw valid conclusions.

One of the best ways to conduct data analysis is with R – a free, popular, open-source software package that was developed for working with data. R is a powerful language used by a growing number of data analysts across all sectors and industries, because analytic professionals without computer programming skills find it relatively easy to use. In this course I will show you how to analyze data with R. You will learn how to organize and explore data, create data visualizations, compute summary statistics, build simple statistical models, conduct statistical tests, and document your analyses so that they could be shared with others.

This is an introductory course, so you don’t need a prior experience with R or statistical training. The skills from this course will provide you with many exciting professional opportunities and competitive advantages.

Let’s get started with Policy Data Analysis.

Yuriy Davydenko, Course Instructor

Yuriy Davydenko, Course Instructor