The course aims at providing the students with the basic tools for modelling and analysing situations that involve uncertainty and will consider applications in various fields. The course will develop a rigorous analysis of finite probability models and provide an introduction to infinite models. The course will cover the following topics: axioms of probability, conditional probability and independence, random variables, random vectors, probability distributions, properties of expectation and limit theorems.
At the end of the term, students will be able to:
- Develop and evaluate simple probabilistic models of engineering systems.
- Have a working knowledge of basics of probability: common distributions and processes, laws of probability and how to apply them, independence and conditional probability, common operations on random variables
- Understand Central Limit Theorem and other limit theorems, and how to apply
- Understand the basics of Poisson processes and its implications in understanding standard queueing models
- Describe and explain the fundamental concepts of probability
- Apply the laws of probability to engineering system problems with uncertainty
- Apply limit theorems to draw inferences from data
Prerequisites: 10.004 Advanced Math II
Prerequisites (for Exchange Students): Multivariable Calculus