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Course Description: Stochastic Processes - Continuous Random Vector - Joint Distribution Function - Marginal and Conditional Distributions - Conditional Expectation and Variance - Distributions of Functions of Random Variables - Joint Moment Generating Functions. Order Statistics - Probability Inequalities - Sequences of Random Variables and Modes of Convergence - Proof of the Central Limit Theorem - Normal Approximation.
Credit hours: 3
Prerequisites: STAT 215
Objectives of the course :

This course aims to give the student an overview of extending the basic concepts and theories of a single random variable to a random vector, as well as familiarizing the student with the concept of convergence of random variables.

Course outputs :

Acquiring knowledge by learning fundamental concepts and theories related to random vectors. Improving the ability to study more than one statistical population in fields where it is needed. Gaining cognitive skills through thinking and solving some real-life problems. Enhancing the capacity for further advanced studies in the field of advanced statistics when necessary.

Additional information:

Introduction to Probability and Mathematical Statistics (Duxbury Classic) by Lee J. Bain and Max Engelhardt (2000)

  • Last updated: 2026-05-13

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