![]() ![]() Course material and presentation will be at an introductory level. This course is the required gateway course for the new major in Data Science & Social Systems. ![]() In-class exercises and problem sets will provide students with the opportunity to use real-world datasets to discover meaningful insights for policymakers and communities. Lectures will introduce students to the methods of data science and social science and apply these frameworks to critical 21st century challenges, including climate change, educational equity, health policy, and political polarization. Students will also consider the ethical dimensions of working with data and learn strategies for translating quantitative results into actionable policies and recommendations. Provides a foundational skill set for solving social problems with data including quantitative analysis, modeling approaches from the social sciences and engineering, and coding skills for working directly with big data. Introduces students to the interdisciplinary intersection of data science and the social sciences through an in-depth examination of contemporary social problems. Freshmen and sophomores interested in data science, computing, and statistics are encouraged to attend. The class will start with a brief introduction to R but will move at a relatively fast pace. Some statistical background or programming experience is helpful, but not required. The objectives of this course are to have students (1) be able to connect data to underlying phenomena and think critically about conclusions drawn from data analysis, and (2) be knowledgeable about how to carry out their own data analysis later. Topics covered include introductions to data visualization techniques, summary statistics, regression, prediction, sampling variability, statistical testing, inference, and replicability. There is a program fee and financial assistance is available for applicants in need. Each week consists of three lectures and two labs, in which students will manipulate real-world data and learn about statistical and computational tools. Two sessions will be offered in 2023: Session 1 (July 10-July 21) will be in-person at the Stanford campus and Session 2 (July 24-August 4) will be held online. classes are crammed into 8 weeks instead of the usual 10-week schedule. Students will engage with fundamental ideas in inferential and computational thinking. I had the incredible opportunity to attend the Stanford summer session last. This course will provide a hands-on introduction to statistics and data science. ![]()
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