Preference Mapping using XLSTAT – 19th March 2024 @ 09:00 (GMT)
Product code: R-Prefmap March 2024
Remote training
March 19, 2024 - March 19, 2024
The remote learning package consists of a lecture delivered online together with workshops for you to complete in your own time (solutions and data sets provided), plus a pdf of the lecture notes and email support whilst you are completing the workshop after the course for up to 2 weeks. More than just a lecture and as close to face-to-face training as it can be!
This module focuses on the statistical techniques and routines available in XLSTAT for relating consumer acceptability to sensory / analytic measures, focussing on application and interpretation of preference mapping, as the technique is more widely known as.
The course content is as follows:
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- What is preference mapping?
- “Internal” mapping v “External” mapping
- Internal mapping using PCA -methods, applications and interpretation
- External mapping using XLSTAT PREFMAP, regression approach, available models
- Mapping using different metrics, overall liking means, cluster means, individual liking scores
- Interpretation of maps, where is my optimal product?
- PREFMAP predictions
- What characteristics does my optimal product have?
- An extensive set of exercises with solutions (explanation of statistics and interpretation of maps) will be included as part of the training.
To be able to perform the exercises you will need a full demo-version of XLSTAT (or licensed copy of XLSTAT Basic + Sensory Methods module).
Length of Session:
Approx 2 hours + workshops
Course Pre-Requisites:
A basic understanding of statistics is assumed i.e. knowledge of statistical terminology and summary measures such as mean, variance, standard deviations.
It would be useful to have attended the Hands on Consumer test data using XLSTAT course or at least have an understanding of common analyses for Consumer Data. Attendance on the Hands On Consumer Test Data course will qualify you for a 10% discount for the Preference Mapping Course.
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$359.64 – $398.88 (Excluding any applicable taxes)