The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
Prerequisites: Open to students enrolled in the M.S. Data Science program or with instructor consent. Recommended preparation: Knowledge of Introductory inferential and descriptive statistics.
Grading Basis: Graded
Research design, ethical and measurement issues as they relate to data science. Measurement topics include: Design of surveys and survey instruments, reliability, validity and generalizability theory. Research design topics include: AB designs, clustering and the identification of internal and external validity threats. Open and reproducible science and ethical conduct of research are themes throughout the course.
Last Refreshed: 08-AUG-22 05.20.26.677896 AM
|Term||Class Number||Campus||Instruction Mode||Instructor||Section||Session||Schedule||Enrollment||Location||Credits||Grading Basis||Notes|
|1228 13446 1 001||Fall 2022||13446||Storrs||In Person||Anglin, Kylie||001||Reg||TuTh 9:30am‑10:45am