Imperial-Computing-Notes

50008 - Probability and Statistics

Course Notes

Module Description

From the college website… In this module you will have the opportunity to:

• use probability theory to model uncertainty
• design simple probabilistic models that facilitate prediction
• conduct sound scientific analysis of data
• use Bayesian inference to refine hypotheses

This module covers the following topics:

• Foundations of probability based on measurable sets
• Discrete random variables and their probability distributions
• Poisson processes
• Continuous random variables and their probability distributions
• Central Limit Theorem
• Generating functions
• Joint random variables
• Estimation
• Hypothesis Testing
• Bayesian inference
• Markov chains

  Lecturers

  Probability (First Half): Professor Giuliano Casale Statistics (Second Half): Professor Chiraag Lala.

  Resources

• College Site

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