Schulung & Webinare

With a focus on sensory analysis methods, from data collection to interpretation using the most relevant tests, this course is intended for marketing, R&D or consumer insight professionals.

This course covers the main methods of sensory analysis and the appropriate statistical analyses, from data collection, through routine processing of sensory and consumer studies (establishment of a sensory profile, panel performance evaluation, segmentation of consumers, etc.) to the processing of specific tests (analysis of multiple tables, preference mapping, ...). The trainer provides numerous examples based on real data to allow the participants to become familiar with the practice of sensory data analysis with XLSTAT-Sensory. An important part of the training is the interpretation of the results. At the end of the course, participants will be able to quickly find and implement the relevant statistical methods to meet their own needs using XLSTAT-Sensory.

Main topics covered in this training:

• Descriptive statistics 
• Statistical tests 
• ANOVA
• PCA, FCA, HAC…
• Preference mapping 
• Discrimination and identification tests

Required experience:

Trainees must have:

• Basic experience using Microsoft Excel

Syllabus:

Introduction: statistics and sensory analysis (sensometrics)

Collecting sensory data:

• Different types of data
• Typical presentation formats: complete blocks, incomplete blocks, Latin squares, Williams designs, MOLS

Descriptive statistics and different visualizations: 

• Unidimensional analysis (main graphs and indicators)
• Bivariate analysis (main graphs and indicators)

Simple product description, relationship between two sensory attributes.

Statistical tests: parametric and non-parametric approaches: 

• Conditions for the use of statistical tests
• Best practices
• Standard tests: Student, Friedman, Wilcoxon, Mann-Whitney, Kruskal-Wallis, etc.

Statistically significant difference between 2 products.

• Analysis of variance (ANOVA)
• One and two factor ANOVA
• Extension to more complex models (more than 2 factors, random effect)

Product effect analysis and multiple product comparisons in a hedonic test; Panel performance study (discriminating power, reproducibility, homogeneity). 

Multivariate analyses:

• Principal Component Analysis (PCA)
• Factorial analysis of simple and multiple correspondences (FCA and MCA)
• Hierarchical Ascending Classification (HAC)

Construction of a sensory "product space"; Definition of product groups, descriptors or consumer segments.

Multiple table analysis:

• Multiple Factor Analysis (MFA)
• Generalized Procustes Analysis (GPA) 

Introduction to holistic and rapid sensory methods (napping, flash profile).

Preference mapping:

• Internal mapping
• External mapping

How to link consumer preferences to product sensory characteristics.

Product discrimination tests:

• Basic principle of discrimination tests
• Overview of the triangle test

A product defect identification test:

• Penalty analysis

Temporal methods for sensory evaluation:

• Basic principle of temporal methods
• Time-Intensity (TI)
• Temporal Dominance of Sensations (TDS)