Statistics for Scientists Advanced
This is a one day advanced course in statistics, relevant to all professionals in the analytical sciences, life sciences and related fields.
- Course delivered face-to-face in one day or online in two half-days
- We limit numbers to 20 per course so that each delegate gets the opportunity to ask questions and fully participate in tutorial exercises
- When delivered on-site we can design the course material to suit your specific training needs
Course Overview | Download course details »
This course is designed for scientists involved in experimental design, decision making and process optimisation. The course shows how to use analysis of variance, randomisation and manipulation of controllable variables to reduce variability, time and cost of design and development.
Course Outline
Quality Control Methods
- Shewhart charts for mean values
- Shewhart charts for ranges
- Warning and action lines
- Cusum charts
- Zone control charts (J-charts)
- Specification setting
Experimental Design and Optimisation
- Introduction
- Randomization and blocking
- Two-way ANOVA
- Latin squares and other designs
- Simulated annealing
- Interactions
- Factorial versus one-at-a-time design
- Factorial design and optimization
- Optimization: basic principles and univariate methods
- Optimization using the alternating variable search method
- The method of steepest ascent
- Simplex optimization
Multivariate Analysis
- Introduction
- Initial analysis
- Principal component analysis
- Cluster analysis
- Discriminant analysis
- K-nearest neighbour method
- Disjoint class modelling
- Regression methods
- Multiple linear regression (MLR)
- Principal components regression (PCR)
- Partial least squares (PLS) regression
- Artificial neural networks