Analytics

Our approach to data analyses is to glean everything we can from the data that has just been collected.  After properly cleaning and editing the data as necessary, we then conduct descriptive statistics (frequencies, crosstabulation) to get a sense of the general story.

When more in-depth analyses is required to get a true sense of group differences or to determine variables that have an impact on certain outcomes, we have the ability to employ the following multi-variate techniques:

  •   Regression/Logistic Regression
  •   HLM Modeling
  •   Discriminant Analysis
  •   Factor Analysis
  •   Cluster Analysis
  •   Perceptual Mapping
  •   Conjoint/Discrete Choice
  •   Max-Diff

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