This course provides a practical introduction to the analysis of high dimensional data, consisting of correlated variables. Many scientific disciplines make use of such techniques for investigating and better understanding large datasets.
Objectives may include data reduction, searching for groupings and classification, which are common aims in the areas of unsupervised and supervised learning. Classic multivariate techniques are introduced and developed, and relationships between them examined. The emphasis will be practical application and interpretation of results using a range of examples. Mathematical details are kept to a minimum. Participants will gain a sound practical understanding of commonly used multivariate techniques.
- Principal Components Analysis (PCA)
- Factor analysis and the use of rotations
- Cluster analysis for grouping objects
- Multidimensional scaling for mapping and its relationship to PCA
- Canonical variates analysis for highlighting differences between groups
- Discriminant analysis and allocation rules
- Correspondence analysis
- Canonical Correlations analysis
DAILY TIMETABLE (subject to minor changes)
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A working knowledge of basic statistics and regression is assumed. Namely; standard deviations, correlation, simple and multiple linear regression
Terms and Conditions
- Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
- Additional discounts are available for multiple registrations.
- Cost includes course materials, lunch and refreshments.
- Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. (Alternatively, laptops can be hired for a fee of £10.00 (ex. VAT) per day).
- If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
- Payment of course fees required prior to the course start date.
- Registration closes 5-calendar days prior to the start of the course.
- 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
- 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
- No fee returned for cancellations made less than 14-calendar days prior to the start of the course.
The number of delegates is restricted. Please register early to guarantee your place.