Statistical and Numerical Methods for Chemical Engineers

Autumn semester 2021

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 24, 2021

Slides

Week	Topic
Week 1 (November 24, 2021)	Simple linear regression Slides: Simple linear regression Recording of the lecture on simple linear regression Lecture Notes (Updated 01.12.21)
Week 2 (December 1, 2021)	Multiple linear regression Slides: Multiple linear regression Recording of the lecture on multiple linear regression Lecture Notes (Updated 08.12.21)
Week 3 (December 8, 2021)	Nonlinear regression Slides: Nonlinear regression Recording of the lecture on nonlinear regression Lecture Notes (Updated 15.12.21) Gauss-Newton algorithm: Geometric interpretation Confidence intervals: Geometric interpretation Summary: Nonlinear regression (15.12.2021)
Week 4 (December 15, 2022)	Design of experiment: Response Surface Methods Slides: Response Surface Methods Recording of the lecture Response Surface Methods Lecture Notes (Updated 22.12.2021) Summary: Response Surface Methods (22.12.2021)
Week 5 (December 22, 2021)	Multivariate Statistics: Principal Component Analysis Slides: PCA Recording of the lecture on multivariate statistics Lecture Notes

Further reading

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