Introduction to Probability

MS&E
120
Instructors
Ha, S. (TA)
Gelauff, L. (TA)
Bistritz, I. (PI)
Lotidis, K. (TA)
Section Number
1
Probability is the foundation behind many important disciplines including statistics, machine learning, risk analysis, stochastic modeling and optimization. This course provides an in-depth undergraduate-level introduction to fundamental ideas and tools of probability. Topics include: the foundations (sample spaces, random variables, probability distributions, conditioning, independence, expectation, variance), a systematic study of the most important univariate and multivariate distributions (Normal, Multivariate Normal, Binomial, Poisson, etc...), as well as a peek at some limit theorems (basic law of large numbers and central limit theorem) and, time permitting, some elementary markov chain theory. Prerequisite: CME 100 or MATH 51.
Grading
Letter or Credit/No Credit
Requirements
GER:DB-EngrAppSci, WAY-AQR, WAY-FR
Units
4
Undergraduate
Course Tags
Advanced Policy Analysis
Academic Year
Quarter
Autumn
Section Days
Monday Wednesday
Start Time
1:30 PM
End Time
3:30 PM
Location
Shriram Ctr BioChemE 104