Statistics & Applied Probability - PSTAT

Overview of data science key concepts and the use of tools for data retrieval, analysis, visualization, and reproducible research. Topics include an introduction to inference and prediction, principles of measurement, missing data, and notions of causality, statistical traps, and concepts in data ethics and privacy. Case studies illustrate the importance of domain knowledge.

Prerequisites: PSTAT 120A; CS 9 or CS 16; and Math 4A, all with letter grade C or better.


PSTAT 100
127 / 125 Full
Data Science Concepts and Analysis
Alexander Franks 5.0
M W
14:00 PM - 15:15 PM
65.8% A