F78ZB - Applied Probability

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Syllabus

1. Joint probability, density and distribution functions

2. Marginal and conditional distributions

3. Expectation of a function of random variables, covariance, correlation

4. Conditional expectation and its uses

5. Markov’s inequality, Chebyshev’s inequality, and introduction to the Central Limit Theorem with applications to statistics

Learning outcomes

By the end of the course, students should be able to do the following:

• Compute the conditional and marginal distributions, as well as their properties, from bivariate random variables.
• Evaluate the relationship between bivariate random variables using their covariance and correlation.
• Apply Markov’s and Chebyshev’s inequalities, as well as the Central Limit Theorem, to approximate probabilities of a random variable.

Further details

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SCQF Level: 8

Credits: 7.5