This two-course sequence is a topics and methods sequence focused on the determinants of human well-being over the short and long-run, with a focus on the interplay between environmental factors and human development. The skills relate to gaining facility with main methods that underlie quantitative research in the environmental social sciences, including econometric concepts related to causal inference, spatial data, machine learning, and data visualization. We expect students to enroll in both quarters of the sequence. The course can be taken for 3-5 units and the expectations for students will be adjusted to reflect credits. See syllabus for difference in expectations. Prerequisite: Working knowledge of R (or comparable programming environment) and some previous exposure to econometric methods or upper-level statistics related to causal inference.
3-5 units · Letter or Credit/No Credit
This two-course sequence is a topics and methods sequence focused on the determinants of human well-being over the short and long-run, with a focus on the interplay between environmental factors and human development. The skills relate to gaining facility with main methods that underlie quantitative research in the environmental social sciences, including econometric concepts related to causal inference, spatial data, machine learning, and data visualization. We expect students to enroll in both quarters of the sequence. The course can be taken for 3-5 units and the expectations for students will be adjusted to reflect credits. See syllabus for difference in expectations. Prerequisite: Working knowledge of R (or comparable programming environment) and some previous exposure to econometric methods or upper-level statistics related to causal inference.
Offered in Winter 2027 at Stanford University.