PSTAT 188: TRNSFR SEM SDS

University of California, Santa Barbara

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 anal ysis. Students will also explore research areas in the discipline, departme ntal and campus study resources, undergraduate research opportunities, and diverse career tracks available to Statistics & Data Science graduates.

Grade distribution records: 17 students across 1 terms.

Grade distribution

Based on 17 student grade records across 1 term and 2 professors.

Instructors

• Ludkovski M 17 students
• Ravat U V 17 students