Spring 2019 not offered
|Certificates: Applied Data Science|
|Course Cluster: Data Analysis Minor, Integrated Design, Engineering & Applied Science Minor|
This course teaches the basic theory of probability. Although the notions are simple and the mathematics involved require only 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 will study are the law of large numbers and the central limit theorem.
||Gen Ed Area Dept:
|Course Format: Lecture / Discussion||Grading Mode: Graded|
||Prerequisites: MATH222 AND MATH228
||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.
|Drop/Add Enrollment Requests|
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