XLSTAT-Conjoint launch and XLSTAT version 2011.3

XLSTAT-Conjoint completes Addinsoft's XLSTAT suite of statistical and analytical software. This add-in is specially cut out for marketers. Conjoint analysis is a method that helps you to find out the expectations of consumers towards new products and to model their choices – both crucial steps of a marketing analysis. Two methods of conjoint analysis are available: full profile conjoint analysis and choice based conjoint analysis (CBC).

XLSTAT-Conjoint is a complete marketing analysis program which allows you to run through all the analytical steps of conjoint analysis which can be divided into five steps:

  1. Choice of the relevant factors and their modalities to describe the products.
  2. Generation of design of experiments based on full factorial, fractional factorial, D-optimal and incomplete block designs.
  3. Collection of the results in Microsoft Excel sheets.
  4. Data analysis with specific regression methods – MONANOVA (monotone regression), multinomial logit, conditional logit, etc.
  5. Simulation of new markets with various methods: first choice, logit, Bradley-Terry-Luce, randomized first choice.

Other additions are completing other existing modules: - The KMO (Kaiser-Meyer-Olkin) statistic has been added to complement the Factor analysis and PCA tools (XLSTAT-Pro) to allow measuring the sampling adequacy. - A new map that automatically superimposes the preference map and a contour plot has been added to the External preference mapping feature of XLSTAT-MX. - XLSTAT-Dose now includes a five parameter parallel lines logistic regression function.


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This module focuses on Analysis of Variance, but this technique makes assumptions about the underlying distributions in our data

This course covers the excellent features in XLSTAT for investigating, visualising and modelling data sets with measurements on many variables.

This short course delivered online will show consumer scientists how to set up and learn about the routines available in XLSTAT for relating consumer acceptability to sensory/analytic measures.

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