statistical analysis
Contributor(s): Stan Gibilisco
Statistical analysis is a component of data analytics.
In the context of business intelligence (BI), statistical analysis involves collecting and scrutinizing every data sample in a set of items from which samples can be drawn. A sample, in statistics, is a representative selection drawn from a total population.
Statistical analysis can be broken down into five discrete steps, as follows:
- Describe the nature of the data to be analyzed.
- Explore the relation of the data to the underlying population.
- Create a model to summarize understanding of how the data relates to the underlying population.
- Prove (or disprove) the validity of the model.
- Employ predictive analytics to run scenarios that will help guide future actions.
The goal of statistical analysis is to identify trends. A retail business, for example, might use statistical analysis to find patterns in unstructured and semi-structured customer data that can be used to create a more positive customer experience and increase sales.
See an introductory Statistics tutorial:
This was last updated in July 2014
Statistics analysis is using the mathematics of probability and uncertainty to make inference about a population, based on a random sample from that population.
"Predictive analytics" and "data analytics" would probably be considered subcategories of statistical analysis.