Spring 2017 not offered
|Certificates: Applied Data Science|
In this course you will learn the basic theory of probability. Although the notions are simple and the mathematics involved only requires a basic knowledge of the ideas of differential and integral calculus, a certain degree of mathematical maturity is necessary. The fundamental concepts to be studied are probability spaces and random variables, the most important ideas being conditional probability and independence. The main theorems we shall study are the law of large numbers and the central limit theorem.
||Gen Ed Area Dept:
|Course Format: Lecture / Discussion||Grading Mode: Graded|
||Fulfills a Major Requirement for: (CADS)(CIS)(COMP)(DATA-MN)(IDEA-MN)(MATH)(MB&B)(NS&B)
Durrett, Richard. ELEMENTARY PROBABILITY FOR APPLICATIONS, ISBN: 978-0-521-86756-6
|Examinations and Assignments: |
|Additional Requirements and/or Comments: |
Students should have a good knowledge of single-variable calculus.
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