|
|
|
||
Application of advanced statistical methods (multivariate observations, pattern recognition methods, regression analysis) to ensure the quality of analytical results and optimization of analytical methods.
Last update: Kania Patrik (24.08.2024)
|
|
||
Doctoral students will be able to:
• use multivariate statistical methods • use linear and non-linear regression • interpret measurement results Last update: Kania Patrik (24.08.2024)
|
|
||
R: Statistics and Chemometrics for Analytical Chemistry (6th Edition), ISBN-13: 978-0273730422, Pearson, 2010 A: Probability & Statistics for Engineers & Scientists, ISBN 978-0-321-62911-1, Pearson, 2012 Last update: Kania Patrik (24.08.2024)
|
|
||
1. Introduction to multidimensional methods 2. Optimization of one-dimensional measurements 3. Optimization of multi-dimensional measurements 4. ANOVA 5. MANOVA 6. Principal component analysis 7. Linear discrimination analysis 8. Correspondence analysis 9. Interaction of epidemiological studies 10. XLSTAT 11. UNSCRAMBLER 12. Regression analysis 13. Nonlinear regression 14. Comprehensive project - assignment and interpretation Last update: Kania Patrik (24.08.2024)
|
|
||
The course is not suitable for students who have already completed the subject M402018 (N402042) Analytical chemometrics. Last update: Kania Patrik (24.08.2024)
|