This course covers the learning outcomes and goals of understanding discrete random variables, including binomial and hypergeometric distributions, probability mass functions, cumulative distribution functions, expected values, variances, and basics of Poisson, negative binomial, and binomial distributions. The course teaches individual skills such as calculating probabilities for discrete random variables and expected values for different types of random variables. The teaching method includes lectures and examples. The intended audience for this course is individuals interested in probability theory and statistics.
Overview
Syllabus
An Introduction to Random Variables.
Binomial Random Variables and the Binomial Distribution (part 1).
Binomial Random Variables and the Binomial Distribution (part 2).
Hypergeometric Random Variables and the Hypergeometric Distribution.
Probabilities for Discrete Random Variables.
Probability Mass Functions.
Cumulative Distribution Functions for Discrete Random Variables.
Expected Value for Discrete Random Variables.
Expected Value for a Binomial Random Variable.
Expected Value for a Hypergeometric Random Variable.
Expected Value of a Function of a Discrete Random Variable.
Variance of a Random Variable.
Variance (Discrete Example).
Poisson Distributions Basics.
Binomial Basics.
Negative Binomial Basics.
Basic Games of Chance.
Taught by
Professor Knudson
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