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3400. Engineering Data Analysis Techniques
3.00 credits
Prerequisites: MATH 1132Q.
Grading Basis: Graded
Introduction to statistics in an engineering context. Core concepts regarding mean, standard deviation, probability density, histograms, cumulative distribution, percentile rank, interquartile range, continuous and discrete distributions (e.g. normal, log normal, exponential, etc.), linear regression, and Bayesian Statistics. Additional topics may be covered based on the engineering discipline of the enrolled students.
Last Refreshed: 25-APR-24 05.20.27.822686 AM
| Term | Campus | Instruction Mode | Instructor | Section | Session | Schedule | Location | Enrollment | Notes | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1243 13490 1 001 | Spring 2024 | Storrs | Online Asynchronous | Tonn, David | 001 | Reg | No Room Required - Online | 28/30 | ||
| 1248 10290 1 001 | Fall 2024 | Storrs | Online Asynchronous | Tonn, David | 001 | Reg | No Room Required - Online | 10/100 |