36-235 Probability and Statistical Inference I
9 units, Carnegie Mellon University
This class is the first half of a two-semester, calculus-based course sequence that introduces theoretical aspects of probability and statistical inference to students. The material in this course and in 36-236 (Probability and Statistical Inference II) is organized so as to provide repeated exposure to essential concepts: the courses cover specific probability distributions and their inferential applications one after another, starting with the normal distribution and continuing with the binomial and Poisson distributions, etc. Topics specifically covered in 36-235 include basic probability, random variables, univariate and multivariate distribution functions, point and interval estimation, hypothesis testing, and regression, with the discussion being supplemented with computer-based examples and exercises (e.g., visualization and simulation). Given its organization, the course is only appropriate for those taking the full two-semester sequence, and thus it is currently open only to statistics majors (primary, additional, dual) and minors. (Check with the statistics advisors for the exact declaration deadline.) Non-majors/minors requiring a probability course are directed to take 36-225 or one of its analogues. A grade of C or better in 36-235 is required in order to advance to 36-236 (or 36-226) and/or 36-410. This course is not open to students who have received credit for 36-217, 36-218, 36-219, or 36-700, or for 21-325 or 15-259. This course is open to those with sophomore standing or higher.
Prerequisites: (21-111 and 21-112) or 21-256 or 21-259 or 21-120
Offered: Fall 2026, Fall 2025
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