Statistical Analysis
Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data.[1] In applying statistics to, e.g., a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.[1]
Statistical Analysis is an aspect of Data Analysis. In the context of Business Intelligence (BI), statistical analysis involves collecting and scrutinising 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.
Contents
Methods
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.
Capability
- Correlation
- Ordinary Least Squares
- R-Squared
- Variance
- Covariance
- Regression Analysis
- ARMA
- ARIMA
- Analysis of Variance, ANOVA
- Outlier Analysis
- Backward Propagation
- Structure Modelling
Technology
Links
Related
- Neural Networks
- Artificial Intelligence
- Machine Learning
- Statistical Analysis
- Technical Analysis