CEE 3040 - Uncertainty Analysis in Engineering


Fall. 4 credits. Student option grading.

Prerequisite: MATH 1910  and MATH 1920 , or equivalents.

R.A. Daziano.

Introduction to statistics and data analysis for engineers. Covers probability theory, discrete and continuous random variables, parametric probability distributions commonly used in engineering practice and research, point estimation, sampling distributions, confidence intervals, hypothesis testing, simple linear regression, and nonparametric statistics. Empirical examples from engineering problems are highlighted.


Textbook: Applied Statistics and Probability of Engineers. Montgomery and Runger, 7th Edition, Wiley. Access to WileyPLUS will be required.

Outcome 1: Introduce students to the basic framework provided by probability theory for analyzing problems exhibiting variability and uncertainty.

Outcome 2: Introduce students to the basic methods and concepts employed in statistics to estimate the parameters of models, make decisions, and to describe uncertainty.

Outcome 3: Prepare students to be able to use statistical methods with confidence during their professional careers (perhaps after further study).

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