Sensory

Chapter 1: Dealing with quantitative perception

This chapter deals with continuous attributes. We introduce the notions of position and dispersion parameters, the concepts of inferential versus descriptive, the comparisons of two means, the notion of model, the analysis of variance, PCA, MFA...

Chapter 2: Dealing with qualitative perception

This chapter deals with categorical variables. We introduce the notions of bar plot, of contingency table, of independence, the magic of Correspondence Analysis...

Chapter 3: Everything you always wanted to know about JAR - a play in five acts

This part was co-written by Alexiane Luc and Sébastien Lê. Thanks for her invaluable help!

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About this course

'Sensory Data Science' is an innovative course about data science applied to sensory data. In this course, we will try to find the right balance between statistics, computer science, mathematics, formalism, intuition, with a pinch of sensory, consumer, perception data. The spirit of the course is as follows: start with data, explore them and introduce the statistical and computer elements necessary to obtain knowledge. Data mining will be done using R software.

About us

The course was created by Sébastien Lê and implemented by Sébastien Lê, Guillaume Béguec, and Marion Moussay, from the statistics and computer science department, Institut Agro Rennes-Angers, CNRS, IRMAR - UMR 6625, F-35000 Rennes, France