CEE 260 / MIE 273
Probability and Statistics in Engineering
University of Massachusetts Amherst
This course introduces probability and statistics with an emphasis on their utility in solving problems relevant to civil, environmental, mechanical, and industrial engineering. Core topics include basic probability concepts, the role of uncertainty in engineering design, sampling and inference (hypothesis testing, confidence intervals, ANOVA), fitting and testing probability distribution models, and regression and correlation analyses.
Offerings
Objectives
CEE 260/MIE 273 aims to introduce statistical methods in engineering and develop your ability to analytically apply these methods in your engineering practice. By the end of the course, you will:
- Understand fundamental concepts of probability, such as independence, expectation, error propagation, and density functions
- Identify, apply, and evaluate appropriate probability models for different systems
- Use statistical methods to describe processes and make inferences about systems from data
- Perform regression analyses, test hypotheses, and calculate confidence intervals to solve engineering problems
- Develop and apply computational and numerical approaches to quantify uncertainty
- Gain proficiency with Python for statistical analysis
Prerequisite
MATH 132 (or equivalent).
Taught by Jimi Oke in the Department of Civil and Environmental Engineering, and affiliated with the NARS Lab.