1.010 Uncertainty in Engineering

Class Info

Introduces probability and statistics with an emphasis on understanding, quantifying, and modeling uncertainty. Topics include events and their probability, the total probability and Bayes' theorems, discrete and continuous random variables and vectors, covariance, correlations, and conditional analysis. 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. Integrates applications with statistical computing and graphics.

This class has 18.02 as a prerequisite.

1.010 will not be offered this semester. It will be available in the Fall semester, and will be instructed by S. Saavedra.

Lecture occurs 9:00 AM to 10:30 AM on Tuesdays and Thursdays in 1-242.

This class counts for a total of 12 credits.

You can find more information at the MIT + 1.010 - Google Search site or on the 1.010 Stellar site.

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