Statistical analysis
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.
Types of Statistical Analysis[edit | edit source]
There are two main types of statistical analysis: descriptive statistics, which describes the main features of a collection of data, and inferential statistics, which involves reaching conclusions from data that are subject to random variation.
Descriptive Statistics[edit | edit source]
Descriptive statistics summarize and organize characteristics of a data set. A data set may include any number of variables, or various pieces of information that certain occurrences are associated with. If a data set includes a large number of observations, descriptive statistics may be used to simplify and present the data in a way that is easy to understand.
Inferential Statistics[edit | edit source]
Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample. That is, inferential statistics uses a small sample of data to say something about what the population might think. Or, inferential statistics helps us to make an educated guess about a population parameter based on a statistic computed from a sample randomly drawn from that population.
See Also[edit | edit source]
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