- Course Prerequisites
- MATH 251 or 253 and ECEN 248
- Course Description
- This course will introduce the student to the fundamental concepts of probability theory applied to engineering problems. Its goal is to develop the ability to construct and exploit probabilistic models in a manner that combines intuition and mathematical precision. The proposed treatment of probability includes elementary set operations, sample spaces and probability laws, conditional probability, independence, and notions of combinatorics. A discussion of discrete and continuous random variables, common distributions, functions, and expectations forms an important part of this course. Transform methods, limit theorems, modes of convergence, and bounding techniques are also covered. In particular, special consideration will be given to the law of large numbers. Examples from engineering, science, and statistics will be provided.
- Course Objectives
- Review basic notions of set theory and simple operations such as unions, intersections, differences and De Morgan’s laws. Discuss Cartesian products and simple combinatorics. Go over the counting principle, permutations, combinations and partitions.
- Understand mathematical descriptions of random variables including probability mass functions, cumulative distribution functions and probability density functions. Become familiar with commonly encountered random variables, in particular the Gaussian random variable.
- Engage the student in active learning through programming challenges, problem solving, and real-world examples. Encourage the student to become an independent learner and increase their awareness of available resources.