3 hours. 2 hours lecture and 2 hours lab per week.
Modeling, Statistical Analysis, and Uncertainty
Course Description
Modeling and analysis of engineering problems under uncertainty
with applications of probability and statistical concepts and
methods. Data collection, measurements, simulation, model
development, misinformation, validation, and analysis with
environmental applications.
Athena Title
Modeling, Statistical Analysis
Prerequisite
MATH 2260
Semester Course Offered
Offered every year.
Grading System
A - F (Traditional)
Student Learning Outcomes
Students will understand the uncertainty inherent to collection of environmental data.
Students will understand simulation and analysis within uncertain environmental problem spaces.
Students will understand the principles and concepts of probability and statistics in analyzing and designing environmental engineering systems.
Students will understand systematic technique for describing uncertainty and realizing risk in environmental applications.
Students will understand quantitative methods for describing direct and indirect relationships among environmental variables.
Topical Outline
Descriptive statistics: Mean
Descriptive statistic: Medians
Descriptive statistic: Variance
Descriptive statistic: Co-variance
Descriptive statistic: Percentiles
Programming in MATLAB: MATLAB Language
Programming in MATLAB: Vectors and Matrices in MATLAB
Programming in MATLAB: Variables, Arrays, and Scripts
Programming in MATLAB: Loops
Probability: Sample spaces
Probability: Assigning probabilities
Probabilities: Outcome
Probabilities: Distribution
Probabilities: Random variable in environmental applications
Probabilities: Independent events
Probabilities: Joint and conditional probabilities
Probabilities: Repeated trials
Combinatorics: Combinatorial methods
Combinatorics: Combinatorial techniques for evaluating probability
