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Uncertainty in Engineering
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CC BY-NC-SA
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This course gives an introduction to probability and statistics, with emphasis on engineering applications. Course topics include events and their probability, the total probability and Bayes’ theorems, discrete and continuous random variables and vectors, uncertainty propagation and conditional analysis. Second-moment representation of uncertainty, random sampling, estimation of distribution parameters (method of moments, maximum likelihood, Bayesian estimation), and simple and multiple linear regression. Concepts illustrated with examples from various areas of engineering and everyday life.

Subject:
Applied Science
Engineering
Mathematics
Material Type:
Full Course
Provider Set:
MIT OpenCourseWare
Author:
Veneziano, Daniele
Date Added:
09/01/2008
Using Grassy Narrows in a Live Classroom with Clicker Questions and Interactive Histogram: Sampling Distributions, Probability, and Hypothesis Testing [version 1.0]
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CC BY-SA
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Students are introduced to concepts of sampling distributions, p-values, and hypothesis testing. Using both simulated and real data for methylmercury level in fish populations, students will determine whether observations fall within government safety guidelines for safe consumption.

Subject:
Biology
Ecology
Life Science
Mathematics
Statistics and Probability
Zoology
Material Type:
Activity/Lab
Lecture
Lesson Plan
Provider:
BioQUEST Curriculum Consortium
Provider Set:
Quantitative Biology at Community Colleges
Date Added:
05/24/2022