Chase Coleman

This course teaches students the Python programming language and helps them understand how writing code can empower them to answer economic questions. Students are taught how to use the “core Python data libraries” like pandas, numpy, and matplotlib. Additionally, there is an emphasis on the fact that “real-world” data are messy; the course presents tools that allow students to thrive in such an environment. Cross-list: ECON 632. Mutually Exclusive: Cannot register for ECON 208 if student has credit for ECON 632.

This course introduces core concepts underlying computational social science, including, optimization, probability, and statistical modeling. We learn how to apply these concepts to a variety of economics and social science questions. Recommended Prerequisite(s): Students should have taken at least a course in calculus and a course in linear algebra. Prior courses in probability and statistics will also be helpful. Highly motivated graduate students lacking some prerequisites can still succeed in this course but will have to put in more time and effort. Such students should meet with us well in advance of the course so that we can recommend readings that will help close the gaps in their preparations. Also, a willingness to consult Wikapedia for math and statistics concepts will help all students. Mutually Exclusive: Cannot register for ECON 631 if student has credit for ECON 308.

This course teaches the foundational skills necessary to do modern data analytics using the Python programming language. We assume that students have previously worked with Python. We will add to existing Python skills and teach the core scientific and data-specific libraries (numpy, scipy, matplotlib, and pandas). We will use these skills to analyze a variety of economics and social science datasets and answer research and business questions. Recommended Prerequisite(s): Students should have prior experience using the Python programming language before starting this course. Throughout this course we will leverage programming skills such as control flow constructs (if/else, for/while), defining custom functions (def), and finding help on existing functions (? in Jupyter environments and help elsewhere). Although a course in probability or statistics is not a prerequisite, students will find some knowledge of these topics to be helpful. Mutually Exclusive: Cannot register for ECON 632 if student has credit for ECON 208.