Multi-Variate Analysis

The multi-variate analysis is the method used to acquire relationships between two different variants with the use of complex statistical techniques. By outsourcing analytics services to DASS, you get a chance to leverage the potential of competent professionals as well as latest technologies in implementing multivariate analysis that further extracts logical results. The quantum of the data doesn't matter as in the age of expansion, DASS is ready to bring out the most useful analysis for your business.

Activities

In the process of multi-variate analysis, we execute some significant activities to help you gain meaningful results. Multivariate analysis undergoes several statistical calculations to relate to multiple variants. These calculative tools are correlation analysis, regression analysis, discriminant analysis, cluster analysis, factor analysis, trade-off analysis, principal component analysis, Jaccard analysis, path analysis, TURF analysis and MaxDiff analysis. Our team also utilizes decision tree techniques like CART (Classification and Regression Trees) and CHAID (CHI Square automatic interaction detection). Apart from all these activities, DASS considers the efficacy of the multi-variate analysis and hence also implies KANO model to provide better support.

How we do it?

The activities we carry out in our multi-variate analysis outsourcing services are listed above, but the procedure we follow while executing the activities is given here:

1. Firstly, we select the imputation required to placed on the position of missing values.

2. Further, we carry quantification and allocation of the range.

3. Then we perform a normality test which helps in identifying the suitability of the model. In this process, if there are any flaws in the distribution and computation of a variable, then it will be found.

4. If there are any negative outliers, then our experts detach it from the main model to have a reliable result of the analysis.

5. Lastly, in our process, we transform all the variables to depict a meaningful observation. This helps in the deriving relationship among the variants.

Key Technologies

  • SPSS

  • SAS

  • R

  • LISREL

  • AMOS

Outcome/Functional Areas

The applicability of multi-variate analysis is mostly seen in the sectors of research especially when it is related to consumer behaviour and market trends. Multi-variate analysis even helps in maintaining the standards of quality in different segments of the industry. DASS, being a prominent provider of research and analysis outsourcing services, helps you in optimizing the process and taking corrective measures in a case of failure. Our experts deploy this analysis into your processes to encourage development and promote social research.