STATS 116 Theory of Probability
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The STATS 116 Theory of Probability course basically introduces students about the fundamentals of probability theory and random processes and illustrates these concepts with engineering applications. This course will exhibit the fundamental principles of random variables and random processes required in applications like signal processing, speech processing, data modeling, digital communications, and so on. MATLAB will be employed as a software tool for bringing probability theory and real-world applications closer altogether.
This STATS 116 Theory of Probability course covers topics like sums of independent random variables, infinitely divisible laws, central limit phenomena, Levy processes, Brownian motion, conditioning, and martingales.
Upon completion of the course, students will be familiar with the following concepts:
- Axioms and basic definitions of probability
- Calculate the probability when the outcome is equally possible, basic combinatorics
- Independence and conditional probability
- Random variables
- Discrete random variable, special distribution
- Continuous random variable, special distribution
- Expectation and variance of random variables
- The law of weak large numbers and the law of strong numbers
- Central Limit Theorem
- Poisson process
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