ORIE 3500 — Eng Probability and Statistics: Modeling and Data Science II
General Information
A rigorous foundation in theory combined with the methods for modeling, analyzing, and controlling randomness in engineering problems. Probabilistic ideas are used to construct models for engineering problems, and statistical methods are used to test and estimate parameters for these models. Specific topics include: random variables, probability distributions, density functions, expectation and variance, multidimensional random variables, and important distributions including normal, Poisson, exponential, hypothesis testing, confidence intervals, and point estimation using maximum likelihood and the method of moments.
Full Cornell course description (FA26)
Credits: 4
Prerequisites and Enrollment
Prerequisites: ENGRD 2700.
Recorded Offerings
| Semester | Listed instructors | Course details |
|---|---|---|
| Fall 2026 | Jamol Pender, Shefali Westfield | Roster / syllabus |
Workload and General Advice
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Course information checked against Cornell’s Spring and Fall 2026 rosters on September 18, 2026. The listed semesters are verified examples, not a complete offering history.