Introduction to Introduction to Sensory Data Analysis - Camo

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6. Summary Summary 1. Managing data from panelists - Evaluation of panel performance 2. Univariate i statistics i 3. Principal component analysis (PCA) 4. Varimax rotation 5. Regression analysis (PCR, PLS, MLR) 6. Preference mapping 7. L-PLS regression 8. Cluster Analysis 9. Classification (SIMCA, PLS-DA) 10. 3-way PLS regression 11. Design of Experiment
6. Summary CAMO Products Product Optimizer The Unscrambler A complete Multivariate Analysis and Experimental Design software. A powerful product formulation and process optimization tool. On‐line applications: •The Unscrambler on‐line •OLUC •OLUP A plug 'n' play product designed to make effective on‐line predictions and classifications, to monitor processes and ensure quality control with spectroscopic measurements. Quali‐Sense The best companion for panel leader detects the personal strengths and weaknesses of each assessor in your panel Training and Consultancy Designed courses and support to help you get the best of your experiments and data
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Introduction to Sensory Data Analys
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Sensory Data Analysis: Course outli
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1. Why sensory data analysis Can we
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1. Why sensory data analysis Sensor
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2. Data collection and experimental
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Page 57 and 58: 5. PLS regression / a) Theory Predi
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