BSOS233

Data Science for the Social Sciences

Prerequisite: MATH115. Restriction: Must be enrolled in the SDS major; or permission of instructor. An introduction to modern methods of data analysis for social scientists. This course emphasizes teaching students who have no previous coding experience how to analyze data and extract meaning in a social science context. Students will gain critical programming skills and learn inferential thinking through examples and projects with real-world relevance.

Spring 2026

4 reviews
Average rating: 4.50

Fall 2025

4 reviews
Average rating: 4.50

Summer 2025

4 reviews
Average rating: 4.50

Spring 2025

4 reviews
Average rating: 4.50

Past Semesters

4 reviews
Average rating: 4.50

1 review
Average rating: 5.00

4 reviews
Average rating: 4.50

1 review
Average rating: 5.00

4 reviews
Average rating: 4.50

1 review
Average rating: 5.00

1 review
Average rating: 5.00

1 review
Average rating: 5.00

0 reviews
Average rating: N/A

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.20 between 359 students*

BSOS233 Grade Distribution+-051015202530354045505560% of studentsABCDFWother
A-: 13.93%
A: 29.81%
A+: 15.04%
B-: 3.9%
B: 7.24%
B+: 10.58%
C-: 2.23%
C: 3.62%
C+: 3.06%
D-: 0.28%
D: 0.28%
F: 3.9%
W: 5.01%
other: 1.11%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.