Spring 2023 Chemical Engineering E4670 section 001

CHEMICAL ENGINEERING DATA ANALYSIS

CHEMICAL ENGINEERING DATA

Call Number 13414
Day & Time
Location
MW 8:40am-9:55am
1127 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Kyle Bishop
Type LECTURE
Method of Instruction In-Person
Course Description

Course is aimed at senior undergraduate and graduate students. Introduces fundamental concepts of Bayesian data analysis as applied to chemical engineering problems. Covers basic elements of probability theory, parameter estimation, model selection, and experimental design. Advanced topics such as nonparametric estimation and Markov chain Monte Carlo (MEME) techniques are introduced. Example problems and case studies drawn from chemical engineering practice are used to highlight the practical relevance of the material. Theory reduced to practice through programming in Mathematica. Course grade based on midterm and final exams, biweekly homework assignments, and final team project.

Web Site Vergil
Department Chemical Engineering
Enrollment 29 students (60 max) as of 8:44PM Wednesday, February 28, 2024
Subject Chemical Engineering
Number E4670
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20231CHEN4670E001