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Computing and Data Analysis for Environmental Applications, Fall 2003

 
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Type: Course Related Materials
Grade Level: Post-secondary
Author: McLaughlin, Dennis B.
Subject: Science and Technology
Institution Name: M.I.T.
Collection Name: MIT OpenCourseWare

Abstract: Covers computational and data analysis techniques for environmental engineering applications. First third of subject introduces MATLAB and numerical modeling. Second third emphasizes probabilistic concepts used in data analysis. Final third provides experience with statistical methods for analyzing field and laboratory data. Numerical techniques such as Monte Carlo simulation are used to illustrate the effects of variability and sampling. Concepts are illustrated with environmental examples and data sets. This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for the analysis of quantitative data in science and engineering. The MATLAB® programming language is used to perform virtual experiments and to analyze real-world data sets, many downloaded from the web. Programming applications include display and assessment of data sets, investigation of hypotheses, and identification of possible casual relationships between variables. This is the first semester that two courses, Computing and Data Analysis for Environmental Applications (1.017) and Uncertainty in Engineering (1.010), are being jointly offered and taught as a single course.

Details

Course Type: Full Course
Material Types: Activities and Labs, Assessments, Homework and Assignments, Lecture Notes, Syllabi
Media Formats: Text/HTML, Downloadable docs
Language: English

Additional Information

Geographic Regional Relevance: All

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