Difference between revisions of "MAT2313"
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* Probability and Counting Techniques | * Probability and Counting Techniques | ||
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|| [[Conditional Probability and Independence]] | || [[Conditional Probability and Independence]] | ||
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* Odds and Conditional Probability | * Odds and Conditional Probability | ||
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+ | * Random Variables | ||
+ | * Probability Mass Function and Cumulative Distribution Function119 | ||
+ | * Expected Value of a Discrete Random Variable | ||
+ | * Expected Value of a Function of a Discrete Random Variable | ||
+ | * Variance and Standard Deviation | ||
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Revision as of 20:52, 25 March 2023
Foundations of Mathematics (3-0) 3 Credit Hours
Course Catalog
Corequisite: MAT1224.
Content: Permutations, combinations, multinational coefficients, inclusion/exclusion principle, axioms of probability, conditional probability, Bayes formula, independent events, discrete random variables, expected value,m variance, discrete random variables (Bernoulli, Binomial, Poisson, geometric, hypergeometric and Zeta random variables), continuous random variables (uniform, normal and other distributions), joint distributions, properties of expectations, limit theorems (Chebyshev's inequality, Central Limit Theorem, Law of Large Numbers)) Generally offered: Fall, Spring, Summer.
Description
Introduction to the theory of probability, through the study of discrete and continuous random variables.
Sample textbooks
- Modern Mathematical Statistics with Applications (Springer Texts in Statistics). Jay L. Devore and Kenneth N. Berk. Second Edition.
- A Probability Course for the Actuaries: A Preparation for Exam P/1, by Marcel B. Finan. Freely available online.
Topics List
Week | Topic | Sections from Finan's book | Subtopics |
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1-2 | Populations and Samples | Chapters 1-2 |
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3-4 | Probability: Definitions and Properties | Chapter 3 |
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5 | Conditional Probability and Independence | Chapter 4 |
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6-8 | Discrete Random Variables | Chapter 5 |
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