Preference Modelling using partial least squares in XLSTAT – 21st March 2024 @ 09:00 (GMT)
Product code: R-Prefmodelling March 2024
March 21, 2024 - March 21, 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 modelling.
The course content is as follows:
- Partial Least Squares (PLS) explained
- Modelling Liking v sensory profile data or analytic data
- PLS approach compared to PCA based PREFMAP
- PLS measures explained (VIP, Q Squared), are PLS confidence intervals reliable?
- RV coefficients as a investigative tool
- Using PLS to link sensory and analytic/instrumental data
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
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 Analysis of Consumer Test Data Course or at least have an understanding of common analyses for consumer data. Delegates attending the Hands on Consumer Test Data course will automatically qualify for a 10% discount on the Preference Modelling course.
$359.64 – $398.88 (Excluding any applicable taxes)