Statistical and Numerical Methods for Chemical Engineers

Autumn semester 2024

General information

Lecturer	Patric Müller
Lectures	Wed 08-10 HG E 33.1 >>
Course catalogue data	>>

Course content

This course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice.

Announcements

Start of the statistical part: November 20, 2024

Slides

Week	Topic
Week 1 (November 20, 2024)	Simple linear regression Slides: Simple linear regression Recording of the lecture on simple linear regression (2023) Recording of the lecture on simple linear regression (2022) Lecture Notes
Week 2 (November 27, 2024	Multiple linear regression Slides: Multiple linear regression Recording of the lecture on multiple linear regression (2023) Recording of the lecture on multiple linear regression (2022) Lecture Notes
Week 3 (December 4, 2024)	Nonlinear regression Slides: Nonlinear regression Recording of the lecture on nonlinear regression (2023) Lecture Notes Gauss-Newton algorithm: Geometric interpretation Confidence intervals: Geometric interpretation
Week 4 (December 11, 2024)	Design of experiment: Response Surface Methods Slides: Response Surface Methods Recording of the lecture Response Surface Methods (2023) Lecture Notes
Week 5 (December 18, 2024)	Multivariate Statistics: Principal Component Analysis Slides: PCA Recording of the lecture on multivariate statistics (2023) Lecture Notes

Exercises

Website

Further reading

Script
Lukas Meier, Wahrscheinlichkeitsrechnung und Statistik, Springer, Berlin, 2020.
W. A. Stahel, Statistische Datenanalyse, Vieweg, 4th edition 2002