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5
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56249
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Lecture-Discussion
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A
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2:00PM
-3:20PM
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TR
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212 David Kinley Hall
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- Availability:
- Closed
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Section Title:
- Experiments in Politics
- Section Info:
- Topic: Experiments in Politics. Instructor: Beatrice Montano. What works? What doesn't? How do we know? Claims about cause and effect are everywhere. Do government job training programs actually raise wages? Does the design of a webpage change what you buy? Does contact with people from a rival group reduce prejudice? Does social media change how you vote? Does exposing a politician's corruption change electoral outcomes? Does female representation in government change which public goods are delivered? These are questions about cause and effect — and answering them rigorously is one of the most valuable skills you can bring to a career in policy, consulting, or business. This course teaches you to evaluate claims about the causes of social trends and to assess whether programs and policies actually work. You will learn why how a study is designed is everything when settling such questions, and why experiments often provide the most convincing evidence. Randomized controlled trials (RCTs) are now the gold standard for answering "what works?" We will get to know the most celebrated experiments in the social sciences: they overturned received wisdom and changed how governments, campaigns, and organizations do their work. Moreover, you will design and carry out your own experiment, turning the logic of experimentation from principle into practice. In a data-driven world where experimentation (also called A/B testing) is at the heart of business, marketing, politics, and policymaking, this course gives you the tools to distinguish rigorous evidence from noise and to design, execute, and analyze experiments that reveal the true causal impact of the interventions and strategies you will spend your career making decisions about.
- Restriction(s):
-
Not intended for students with Freshman class standing.
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3
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56260
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Lecture-Discussion
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FV
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1:30PM
-2:50PM
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MW
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223 David Kinley Hall
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Vasselai, F
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- Availability:
- Open (Restricted)
- Part of Term:
- 1
- Date Range:
- 08/24/26-12/09/26
- Section Title:
- Intro Data Science for Soc Sci
- Section Info:
- Intro to Data Science Techniques for Social Scientists. This course is designed as a gentle, applied introduction to key computational concepts and techniques in Data Science, geared towards Social Scientists. The rapid increase in the variety and sophistication of available tools is transforming the Social Sciences, making them increasingly computational. The course aims to provide students, even those with little quantitative background, with the knowledge and skills necessary to: 1. understand and apply basic versions of a variety of data science techniques; 2. pursue further training in those methods if they wish. The first part of the course will be a mildly fast-paced introduction to the R programming language, commonly used in data analysis and statistics. In the second part, students will learn critical Data Science techniques such as: data handling and cleaning, data visualization, web scraping, pseudo-random number generation, Monte Carlo simulations, the basics of text analysis, and the basics of network analysis. The third and final part of the course covers how computer hardware works, how to use the computer terminal, how to leverage High-Performance Computing (HPC) through parallel computing (locally and in the cloud), how to handle big data, and how to control code versions. All topics will be approached with Social Science works and research in mind, and most will be illustrated with Political Science examples. Having taken PS 230 or having had a previous, introductory, contact with R (or with other program languages) is recommended but not required. Feel free to email the faculty (vasselai@illinois.edu) with questions about your specific case.
- Restriction(s):
-
Not intended for students with Freshman class standing.
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