Foundations of probability, conditioning, and independence. Business, computing, biological, engineering reliability, and quality control applications. Classical discrete and continuous models. Pseudo-random number generation. Prerequisites: MATH 020 or MATH 022 or MATH 023.
Dates: May 20 - July 12, 2019
Two semesters of calculus are a prerequisite for this course. In order to understand real world phenomena, it is necessary to account for the role of randomness. Probability provides a framework to understand and model randomness. Topics will include: axioms of probability, basic combinatorics, conditional probability and independence, distributions of random variables, mathematical expectation, and functions of random variables.
Textbook: Probability & Statistical Inference by Hogg, Tanis & Zimmerman. (Don't get the "Global Edition" because the problems are different from the U.S. version!) A printed copy is rather expensive, but the e-book is a less expensive option and is sufficient.
Grades will be determined based on the following criteria: Discussion Board Participation 10% Quizzes 40% Exams 50%
Online Course (View Campus Map)
Note: These dates may change before registration begins.
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|STAT 111 OL2||Statistics: QR: Elements of Statistics (online)||to||N/A||See Notes||3||61782|
|STAT 141 OL1||Statistics: QR:Basic Statistical Methods 1 (online)||to||N/A||See Notes||3||61780|
|STAT 141 OL2||Statistics: QR:Basic Statistical Methods 1 (online)||to||N/A||See Notes||3||61781|
|STAT 183 OL1||Statistics: QR:Basic Statistical Methods 2 (online)||to||N/A||See Notes||3||61774|
|STAT 211 OL1||Statistics: QR: Statistical Methods I (online)||to||N/A||See Notes||3||61785|
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