EcDS_syllabus-8.pdf - 73-265 Economics Data Science Professor John Gasper Fall 2018 Updated Course Time Location Tues\/Thur 3:00-4:20pm Room TPR 2612

EcDS_syllabus-8.pdf - 73-265 Economics Data Science...

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73-265: Economics & Data Science Professor John Gasper Fall 2018 Updated: August 27, 2018 Course Time / Location : Tues/Thur 3:00-4:20pm; Room: TPR 2612 Instructor : John Gasper Office : TPR 4202 Email : [email protected] Office Hours : Tues/Thur: 4:30-5:30pm; Wednesday 2 - 3pm; by appointment In general, I have an open door policy: if my door is open and I’m not meeting with someone, you are welcome to come in and meet with me. If my door is closed, I am not available (out of the office, working, etc). I know finding office hour times that work for everyone is difficult. Consider these a suggested meeting time, but I highly encourage you to schedule an appointment . Please, don’t interpret a closed door as me not wanting to meet with you. I do, but just send me an email to schedule some time. Teaching Assistants : Mason Paccione Office hours: TBA Required materials : Clicker(either the device or app for your phone) R for Data Science , Grolemund and Wickham Storytelling with Data , Knaflic website for book Mastering Metrics: the Path from Cause to Effect , Angrist and Pischke Suggested Supplemental Texts : Introductory Econometrics: A Modern Approach , Wooldridge. Mostly Harmless Econometrics: An Empiricist’s Companion , Angrist and Pischke 1
Course Description and Goals This course is at the intersection of economic analysis, computing, and statistics. It develops foundational skills in these areas and provides students with hands-on experience in identi- fying, analyzing, and using data to solve real-world problems in economics and business. In this course we will be using the statistical programming language R, which is a pow- erful open-source language that is widely used. In this very hands-on, data-centric, course, students will learn the basics of data manipulation, how to visualize, present and interpret data related to economic and business activity by employing statistical analysis and various visualization techniques. Through many interactive exercises, students will develop a foundation for data-driven decision making. This course also provides a solid base for future courses such as Econo- metrics I and II (73-274/275) that provide a rigorous treatment of more advanced methods used for business, economics, and public policy. The exact data sets we will use will vary and depend on student interest, but the underlying objectives of the course will remain: Develop competence in the statistical programming language R and manipulating data. Develop competence in visualizing data using R. Perform various statistical analyses used in economic analysis Interpret the estimates from these statistical analyses. Develop communication skills to effectively describe and visualize findings for technical and non-technical audiences.

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