Introduction to Probability and Statistics
Course Description
This course provides an elementary introduction to probability and statistics with applications. Topics include: basic combinatorics, random variables, probability distributions, Bayesian inference, hypothesis testing, confidence intervals, and linear regression.
These same course materials, except for the interactive elements, are also available on the MIT OpenCourseWare site.
This course is brought to you by MIT OpenCourseWare and provided under our Creative Commons License.
Prerequisites
Course Instructors
Dr. Jeremy Orloff, MIT
For many years until June 2022 Dr. Jeremy Orloff was a lecturer at MIT in both the Mathematics Department and the Experimental Study Group (ESG). In June 2022 he retired from the Math Department, but continues to teach in ESG. This OCW version is from the last of the many times he taught 18.05.
Dr. Jennifer French Kamrin, MIT
Dr. Jennifer French Kamrin is a digital learning scientist. She developed online content and problems using the edX platform; created an interactive course text for the differential equations course; and also developed online problem set components for calculus, differential equations, and linear algebra used residentially at MIT.