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Multivariate Techniques for Sensory and Consumer Studies MTSC |
 Duration : 3.0 day(s) | |
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:: Course SummaryThis 3-day session is targeted towards sensory and consumer scientists interested in an applied workshop on multivariate data analysis of sensory and consumer test data with a strong emphasis on graphical summary representations.
During the first two days, classical multivariate techniques including Principal Component Analysis (PCA), Factor Analysis, Correspondence Analysis, Cluster Analysis and Discriminant Analysis are presented and their usefulness for sensory and consumer data is illustrated with case studies based on real data.
The last day is dedicated to alternative and less known applications of these methods to address specific issues and get more actionable results from the collected data. For instance:
PCA to measure panelist agreement in sensory attributes understanding
Extended Preference Mapping for the identification of niche products & sensory drivers
Discriminant analysis for product and concept mapping
A combination of PCA and cluster analysis to select a subset of representative products in a larger series of samples.
Throughout the workshop, participants are encouraged to use their own software and data to apply the multivariate techniques. Experienced instructors who have more than 15 years experience in the design and analysis of sensory and consumer test data will assist participants. They are very knowledgeable and proficient with most statistical packages.:: Learning ObjectivesUpon completion of this course, participants will be able
To understand the general mechanism of multivariate statistical methods used for sensory product development and testing
To understand which multivariate technique(s) to use to address typical issues in sensory and consumer tests
To perform the multivariate analyses with their own software
To extract the relevant information from the statistical software output
To interpret results and to create graphical summaries of the data/LI>
To know what are the common pitfalls in the use and interpretation of the multivariate tools/LI>
To summarize and communicate the results with more confidence:: Target AudienceThis workshop is targeted towards:
Sensory scientists
Consumer insights staff
Statisticians who work on sensory and consumer data:: PrerequisiteTo attend this course, participants must have:
Completed the course Fundamental Tools in Statistics or an equivalent course so that they possess a working knowledge of basic concepts in statistics: descriptive statistics (mean, standard deviation, correlation coefficients, etc.), the different types of variables (continuous vs. discrete)
A basic knowkedge of Principal Component Analysis (PCA) is desirable, but it is not mandatory as the general mechanism of the technique will be covered in the workshop
Participants using their own software must have a good working knowkedge of their software inferface: they must know how to import a Microsoft EXCEL file, create new variables, etc.:: Notes and Other InformationSome association members are entitled to discounted registration fees. During the online registration process, do not forget to mention the association name, your membership number and the registration fees will be adjusted if you are entitled to a discount. | | |
:: Topics CoveredDay 1
- Principal Component Analysis (PCA): A Tool to Identify and Depict Data Redundancy
- Common Misinterpretations of PCA Biplots
- Applications of PCA for visual panel performance assessment
- Applications of PCA for consumer mapping with Internal Preference Mapping
- Factor Analysis (FA): A Tool to Extract Latent Variables/Underlying Dimensions
- The similarities and dissimilarities of PCA and Factor Analysis. When should each technique be used, and why?
- Applications of FA for determining the data dimensionality
- Applications of FA for extracting products' underlying dimensions
- Simple and Multiple Correspondence Analysis (SCA and MCA)
- The correct interpretation of SCA and MCA Biplots
- Applications of SCA and MCA for quantitative marketing projects and for the visualisation of questionnaire data
Day 2
- Cluster Analysis: A Tool to Create Groups of Homogeneous Objects
- Agglomerative Hierarchical Clustering Methods and K-Means
- Applications of cluster analysis for customer segmentation, product mapping and creating groups of products
- Discriminant Analysis (DA): A Tool to Identify the Most Important Characteristics that Help Distinguish Products/Concepts
- Applications of DA for finding the most discriminating product characteristics and mapping of products and concepts
Day 3
- Original Methods and Applications of Multivariate Techniques in Sensory and Consumer Research
- Applications of PCA for the idenfication of sensory drivers with Extended Preference Mapping
- Applications of CA for the idenfication of the ideal product/concept characteristics
- Applications of PCA and Cluster analysis for customer segmentation visualization
- Hands-On Applications: Sample datasets will be given to participants. However, participants are strongly encouraged to bring their own laptop, favourite statistical package and data to fully harness the power of multivariate data analysis tools.
:: Course ContentThis 3-day workshop presents the most popular multivariate techniques to address typical questions in sensory and consumer science. The following techniques are covered:
- Principal Component Analysis (PCA)
- Factor Analysis
- Correspondence Analysis
- Cluster Analysis
- Discriminant Analysis
Throughout the workshop, emphasis will be placed on :
- The purpose of each method
- The type of data required
- The advantages and limitations
- The type of results provided by each technique
Real-life examples from sensory and consumer research will be used to illustrate the power of the multivariate tools.
In-depth explanations of the graphical software output is provided for each method to ensure a concrete understanding of how these methods work and what they have to offer. For each method, hands-on workshops will take place to give participants the opportunity to assimilate the tools learned using their own software and their own data so that they can make the most out of the training.
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Upcoming Public Sessions |
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| No public session is scheduled yet, contact us if you are interested. |
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Offered Discounts- Register more than 6 weeks before a session date and get a 15% discount (Displayed above if available).
- Register 2 persons or more and get a 10% discount (Applied at checkout).
- Register for 2 sessions or more and get a 10% discount (Applied at checkout).
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Multivariate Data Analysis School |
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