Introduction to Introduction to Sensory Data Analysis - Camo

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3. Inspection and preparation of the data / a) Theory Example data set: Tomatoes 17 tomato varieties (products) 11 descriptive evaluations (attributes) grade: 0 to 10 14 trained assessors (panelists)
3. Inspection and preparation of the data / a) Theory Quali-Sense
Page 1 and 2: Introduction to Sensory Data Analys
Page 3 and 4: Sensory Data Analysis: Course outli
Page 5 and 6: 1. Why sensory data analysis Can we
Page 7 and 8: 1. Why sensory data analysis Sensor
Page 9 and 10: 2. Data collection and experimental
Page 13: 3. Inspection and preparation of th
Page 17 and 18: 3. Inspection and preparation of th
Page 31 and 32: 4. Principal Component Analysis: PC
Page 47 and 48: 4.Principal Component Analysis: PCA
Page 49 and 50: 5. PLS regression / a) Theory Regre
Page 51 and 52: 5. PLS regression / a) Theory Examp
Page 53 and 54: 5. PLS regression / a) Theory Do a
Page 55 and 56: 5. PLS regression / a) Theory Sampl
Page 57 and 58: 5. PLS regression / a) Theory Predi
Page 63 and 64: 6. Summary CAMO Products Product Op

Introduction to Introduction to Sensory Data Analysis - Camo

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