Course Detail

Units:

3.0
Course Components:

Lecture

Enrollment Information

Enrollment Requirement:

Prerequisites: 'C-' or better in (MATH 1220 OR MATH 1320 OR MATH 1321 OR AP Calc BC score of 4+) AND (Full Major status in Computer Science OR Computer Engineering OR Electrical Engineering OR Data Science OR Software Development

Requirement Designation:

Quantitative Intensive BS

Description

An introduction to probability theory and statistics, with an emphasis on solving problems in electrical and computer engineering. Topics in probability include discrete and continuous random variables, probability distributions, sums and functions of random variables, the law of large numbers, and the central limit theorem. Topics in statistics include sample mean and variance, estimating distributions, correlation, regression, and hypothesis testing. Engineering applications include failure analysis, process control, communication systems, and speech recognition.