401-0675-00L Statistical and Numerical Methods for Chemical Engineers
Semester | Autumn Semester 2023 |
Lecturers | R. Käppeli, P. Müller, C.‑J. Shih |
Periodicity | yearly recurring course |
Language of instruction | English |
Abstract | This course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice. | |||||||||
Learning objective | This course covers common numerical algorithms and statistical methods used by chemical engineers to solve typical problems arising in industrial and research practice. The focus is on application of these algorithms to real world problems, while the underlying mathematical principles are also explained. The MATLAB environment is adopted to integrate computation, visualization and programming. | |||||||||
Content | Topics covered: Part I: Numerical Methods: - Interpolation & Numerical Calculus - Non-linear Equations - Ordinary Differential Equations - Partial Differential Equations - Linear and Non-linear Least Squares Part II: Statistical Methods: - Data analysis and regression methods - Statistical experimental design - Multivariate analysis | |||||||||
Lecture notes | For the numerics part, see http://www.sam.math.ethz.ch/~karoger/numci/2023/ For the statistics part, see http://stat.ethz.ch/lectures/as23/statistical-numerical-methods.php | |||||||||
Literature | Recommended reading: 1) U. Ascher and C. Greif, A First Course in Numerical Methods, SIAM, Philadelphia, 2011 2) K. J. Beers, Numerical Methods for Chemical Engineering : Applications in MATLAB, Cambridge : Cambridge University Press, 2006 3) W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, Numerical Recipes, Cambridge University Press 4) W. A. Stahel, Statistische Datenanalyse, Vieweg, 4th edition 2002 | |||||||||
Competencies |
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