COURSE OVERVIEW
Who is this course for?
This course is suitable for method developers who wish to use statistical software to improve the development and optimization of methods and to have a greater understanding of the results generated by the techniques.
What you will learn
- Setting method development objectives
- Full Factorial Designs and Screening Designs
- Optimisation of Factors
- Application of Multivariate techniques for complex datasets
COURSE OUTLINE
Experimental Design and Optimisation
- Introduction
- Scale of method development
- Randomisation and blocking
- Two-way ANOVA
- Latin squares and other designs
- Interactions
- Factorial versus one-at-a-time design
- Factorial design and optimisation
- Optimisation: basic principles and univariate methods
- Optimisation using the alternating variable search method
- The method of steepest ascent
- Simplex optimisation
- Simulated annealing
Multivariate Analysis
- Introduction
- Initial analysis
- Principal component analysis
- Cluster analysis
- Discriminant analysis
- K-nearest neighbour method
- Regression methods
- Multiple linear regression (MLR)
- Principal components regression (PCR)
- Partial least squares (PLS) regression