Certainly multinomial analysis can help when you are examining a range of categorical outcomes: A, B, C or D. But binary analysis — yes or no, present or absent — is more often used. Although the outcomes are constrained, the possibilities are not. Binary logistic regression can be used to examine everything from baseball statistics to landslide susceptibility to handwriting analysis.
This approach to analytics also proves useful for a range of statistical concepts and applications:
- Text analytics
- Chi-square automatic interaction detection (CHAID)
- Conjoint analysis
- Bootstrapping statistics
- Nonlinear regression
- Cluster statistics and cluster analysis software
- Monte Carlo simulation
- Descriptive statistics
The use of statistical analysis software delivers great value for approaches such as logistic regression analysis, multivariate analysis, neural networks, decision trees and linear regression. But remember: hardware and cloud - computing solutions should also be considered if you need to accommodate large data sets either on premises, in the cloud or in a hybrid cloud configuration.