×

Warning

The RokSprocket Module needs the RokSprocket Component enabled.

Measuring and Reporting Descriptive Panel Performance

Measuring and Reporting Descriptive Panel Performance

This workshop on Measuring and Reporting Descriptive Panel Performance first introduces indicators designed to capture the desirable attributes of descriptive data collected by a trained sensory panel (agreement, repeatability and discrimination power). A suite of statistical tools are used to depict and quantify the performance of the panel.

Real-life case studies are used to illustrate the principles of the statistical tools and the insights that may be extracted from the data. 

 

Course Details

Learning Objectives

Learning Objectives:

Upon completion of this module, participants will be able:

  • To know what criteria are use to assess panel performance
  • To know which statistical tools are relevant for measuring the criteria
  • To understand how to appropriately format the data for each analysis
  • Conduct a sensory panel performance study
  • To read and interpret numeric and graphical software output
  • To report and communicate the results of the analyses
  • Take appropriate action to correct any problems detected

Target Audience

Target Audience:

Professionals using descriptive sensory data in their work and who want to learn practical ways to measure the performance of sensory panelists.

Prerequisite

Prerequisite:

Knowledge of basic principles of descriptive analysis is recommended (Fundamental Tools in Statistics). Moreover, working knowledge of ANOVA and the multivariate analysis PCA is also recommended.

Course Outline

Course Outline:
  • Definition of Performance Measurement Criteria
  • Graphical Exploratory Tools & Descriptive Statistics
  • Use of ANOVA to Measure Panel Performance
  • Use of the Principal Component Analysis (PCA) to Visually Assess Performance
  • Case Studies
  • Summary

Practical Info

Practical Info:

Recommended Course Duration: 1 day

Related Sessions

  • An applied set of modules with focus on the most widely used multivariate methods and their applications in several fields of application. Learn about the principle of the methods, the data needed, and the information they provide.

  • Learn about preference mapping techniques to explore and understand consumer preferences. Applications dealing with segmentation and the identification of niche markets are discussed. Focus on pitfalls and good practices.

  • Understanding consumers and their preferences is crucial for competitive businesses. Learn about commonly used methods to analyse consumer test data, the way to interpret results and to communicate them with insightful graphical summaries.

  • Discover a powerful multivariate technique for mapping the consensus among assessors rating series of products/concepts, and for quantifying and mapping the redundancy in sensory descriptors.