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Hauptkomponentenregression
What is Principal Component Regression PCR (Principal Components Regression) is a regression method that can be divided into three steps: The first step is to run a PCA (Principal Components Analysis) on the table of the explanatory variables, Then run an Ordinary Least Squares regression (OLS regression) also called linear regression on the selected components, Finally compute the parameters of the...
Hauptkoordinaten-Analyse (HKoA)
Benutzen Sie die Hauptkoordinaten-Analyse (auf englisch Principal Coordinates Analysis genannt), um eine quadratische Matrix, die die Ähnlichkeit oder die Unähnlichkeit zwischen p Elementen (Individuen, Variablen, Beobachtungen, …) beschreiben, grafisch darzustellen.
Panelanalyse
Use of Panel Analysis Use this tool to check whether your sensory or consumer panel allows to differentiate a series of products. If it does, measure to what extent and make sure that the ratings given by the assessors are reliable. Eight different types of analyses are performed so that you have a clear idea of how your panel performs whether globally or product by product. This unique feature saves...
Internes Präferenzmapping
What is preference mapping? Preference Mapping allows to build maps which show the preference of consumer for a type of product. A preference map is a decision support tool in analyses where a configuration of objects has been obtained from a first analysis (PCA, MCA, MDS), and where a table with complementary data describing the objects is available (attributes or preference data). There are two...
Partielle Kleinste Quadrate Regression (PLS)
Partial Least Squares regression (PLS) is a quick, efficient and optimal regression method based on covariance. It is recommended in cases of regression where the number of explanatory variables is high, and where it is likely that the explanatory variables are correlated. What is Partial Least Squares regression The idea behind the PLS regression is to create, starting from a table with n observations...
Analyse von CATA-Daten
What is CATA (check-all-that-apply) analysis? CATA (check-all-that-apply) surveys have become more and more popular for sensory product characterization since 2007, when it was presented by Adams et al. CATA surveys allow to focus on consumers, more representative of the market, instead of trained assessors. They are easy to set up and easy for participants to answer. The principle is that each assessor...