Multivariate Analysis - Level 1
M201 - 2 days
The world is Multivariate and, as a result, MVA of complex datasets is practised in almost all types of manufacturing sectors and research-based institutions. This workshop introduces the powerful methods and tools that are available to help you to turn large complex multivariate data into informed decisions. The workshop features the Unscrambler®X software package from CAMO.
- Introduction to Multivariate Data Modelling
- Principles and applications of Principal Components Analysis (PCA)
- Multivariate regression:
- Multilinear regression (MLR)
- Principal Components Regression (PCR)
- Partial Least Squares (PLS)
- Relevant data collection
- Pretreatment and scaling
- Detecting and dealing with Outliers
- Basic rules for successful data analysis
Software Tools Used
Attendees may also be interested in exploring Prism's free online 3D Visualiser tool.
Who should attend?
- Scientists, Engineers, Statisticians, Spectroscopists, Chemometricians and others involved in the following disciplines or functions:
- Consumer insights
- Product development
- Process optimisation
- Quality control & monitoring
- Working with spectroscopic instruments
- NIR, FTIR, UV, UV/VIS, NMR, DAS, Raman, Mass Spectoscopy
- Working with chromatography instruments
- LC, CE, GC, HPLC
- Production data & sensory data
- Production processes
This is an introductory workshop. No prior knowledge of the Unscrambler®X is required.
Upcoming public deliveries of this workshop...
To view our full public training programme, please click here.
|21 - 22 May 2019||Multivariate Analysis - Level 1||The Unscrambler® from CAMO||Stansted||Contact us||Reserve now|
|19 - 20 November 2019||Multivariate Analysis - Level 1||The Unscrambler® from CAMO||Stansted||Contact us||Reserve now|
Note: public deliveries of this workshop are offered in collaboration with an external partner, so our partner's prices, discounts, cancellation policy and other T&Cs will be applied instead of our own. Please contact us for more information.