You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
- Author:
-
Sheffield, Scott
- Subject:
- Mathematics and Statistics
- Institution Name:
- M.I.T.
- Collection:
-
MIT OpenCourseWare
- Grade Level:
- Post-secondary
- Abstract:
This course introduces students to probability and random variables. Topics include distribution functions, binomial, geometric, hypergeometric, and Poisson distributions. The other topics covered are uniform, exponential, normal, gamma and beta distributions; conditional probability; Bayes theorem; joint distributions; Chebyshev inequality; law of large numbers; and central limit theorem.
- Languages:
- English
- Material Type:
- Assessments, Full Course, Homework and Assignments, Lecture Notes, Readings, Syllabi
- Media Format:
- Text/HTML, Downloadable docs
- Conditions of Use:
-
Creative Commons Attribution-Noncommercial-Share Alike 3.0
- Copyright Holder:
- Massachusetts Institute of Technology
No restrictions on your remixing, redistributing, or making derivative works.
Give credit to the author, as required.
Your remixing, redistributing, or making derivatives works comes with some
restrictions, including how it is shared.
Your redistributing comes with some restrictions. Do not remix or make
derivative works.
Copyrighted materials, available under Fair Use and the TEACH Act for US-based
educators, or other custom arrangements. Go to the resource provider to see
their individual restrictions.
Comments