Free Textbook
R for Data Science
Data Science for Sensory and Consumer Scientists
Chapman & Hall/CRC (Data Science Series) · September 2023 · 348 pages
About the Book
A practical guide to data science using R covering data manipulation, visualization, machine learning, text analysis, and dashboards, all applied to real sensory and consumer science case studies.
Written for sensory and consumer scientists working inside large organizations with backgrounds in food science, psychology, marketing, and chemical engineering. The book assumes little to no coding experience and guides readers through R using a creative restaurant-menu structure, from Apéritifs through Digestifs.
What's Inside
Structured like a French restaurant menu, the book takes you from appetizer-level introductions through to advanced main courses.
Getting Started
Tips, tricks, and tools to get accustomed to R and the overall style of the book.
Core Skills
In-depth exploration of the core tools used frequently throughout the book: data wrangling, plotting, and reproducible reports.
The Biscuit Study
The complete workflow applied to a real-world case study on biscuits, from collecting data through to delivering actionable insights.
Advanced Topics
Extending the workflow to other types of data and more advanced analysis techniques including ML, NLP, and interactive dashboards.
Looking Forward
Relevant extensions and next steps that complement the core material covered in the book.
Meet the Authors
Dr. Thierry Worch
Sensometrician & Data Scientist
An accomplished expert in sensory and consumer research with a PhD on the Ideal Profile Method. He has made significant contributions to software development in sensometrics and is a data scientist at FrieslandCampina.
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Dr. Julien Delarue
Associate Professor, UC Davis
A leading expert in sensory perception and food design, bringing academic rigor and research methodology expertise to the intersection of food science and data analytics.
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Dr. Vanessa Rios de Souza
AigoraDirector of Client Solutions, Aigora
A highly skilled food scientist with over 10 years of experience in R&D, consumer and sensory research. With 70+ scientific publications, she combines deep technical expertise with practical insight to guide companies through their AI adoption journey.
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Dr. John Ennis
AigoraCEO & AI Pioneer, Aigora
A versatile researcher, author, and entrepreneur with over 30 years in sensory science, a PhD in Mathematics, and a postdoctoral focus on AI. Author of 50+ publications and 4 books, he has shaped R&D capabilities at Fortune 500 companies globally.
LinkedInPodcast Episodes
Listen to these podcasts created with NotebookLM exploring key concepts from the book.
Episode 1: Apéritifs
This introductory episode establishes the target audience (sensory and consumer scientists with little to no coding experience) and the core goal: helping practitioners transition into computational sensory science. It emphasizes that the book is not a statistics manual but a guide to building a solid, reproducible data science workflow.
Episode 2: Hors d'oeuvres
This episode explores the foundational mechanics of the R environment. It covers the importance of setting up projects, establishing version control (using tools like GitHub), and the pedagogical philosophy of learning code like a new language through active, hands-on practice.
Episode 3: Bon Appétit
The "main course" of the series. It illustrates the entire proposed data science workflow, from experimental setup and cleaning to analysis and communication, by applying it to a concrete, relatable case study involving consumer testing of biscuits.
Episode 4: Haute Cuisine
Aimed at the "gourmands" (advanced learners), this episode explores how the foundational workflow established in the biscuit study can be scaled and applied to significantly more complex, non-linear, and multi-dimensional sensory data structures.
Episode 5: Digestifs
The series finale wraps up by discussing advanced topics such as text mining, predictive modeling with machine learning, and interactive data visualization using tools like Shiny. It concludes with the goal of making practitioners confident, independent data scientists.
Start Your Data Science Journey
The full book is now available to read online for free. Or pick up a physical copy and follow along with the companion code.
Want to go further? Explore our AI Course or watch the free Masterclass.