Statistics & Applied Probability - PSTAT

Introduces students to foundational programming concepts for data analysis and visualization and fundamental concepts in probability and mathematics (random variables, set theory, simulations, series and integration), serving as preparation for follow-up major gateway courses in PSTAT. The material is organized into distinct modules and includes a brief introduction to R, Python, tidy data framework, data science ethics, and exploratory data analysis. Students will also explore research areas in the discipline, departmental and campus study resources, undergraduate research opportunities, and diverse career tracks available to Statistics & Data Science graduates.

Prerequisites: New transfer students only; department approval required to finalize registration.


PSTAT 188
0 / 25 Enrolled
Transfer Exploration Seminar: Statistics and Data Science
Michael Ludkovski 3.3 Uma Ravat 2.3
T R
14:00 PM - 15:05 PM