Carnegie Mellon University

Probability and Statistics

Course Number: 45750

This course introduces tools for decision making under uncertainty, ranging from the fundamentals of probability theory, decision theory and statistical models to simple software for data analysis. Topics include statistical independence, conditional probability, Bayes theorem, discrete and continuous distributions, expectation and variance, decision trees, sampling and sampling distributions, interval estimation, hypothesis testing, p-value, correlation and simple regression.
(GC-2014)

Degree: MBA
Academic Year: 2019-2020
Semester(s): Mini 1
Required/Elective: Required
Units: 6

Format

Lecture: 100min/wk and Recitation: 50min/wk