What is Classical Statistics?

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What is Classical Statistics and how can it be applied to your company or industry?

Classical statistics is the foundation of numerous data analysis, modeling, and forecasting techniques. It is used to discover relationships and uncover trends found in numerical data, providing valuable insights to guide further decision making. Classical statistics is also used to guide and develop data collection techniques, such as in clinical trial design or other experimental design, and in manufacturing quality control.

Classical statistical techniques power a multitude of data analyses aimed at uncovering relationships between numerical variables, including:

• Descriptive statistics
  • Information that summarizes data such as mean (average), median, minimum and maximum values, and standard deviation
• Hypothesis testing
  • Comparison of two or more data samples against a hypothesis – a typical example is the t-test, which tests the hypothesis that the mean of two samples is the same
• Correlation analyses
  • Determines the strength of a relationship between two data samples
• Regression analysis and Predictive modeling
  • Determines the relationship between an outcome variable and one or more predictor variables, how strongly the predictors relate to the outcome, and use those relationships to predict future outcomes
• Clustering analyses
  • Classifies variables into groups based on how similar they are

Contact us to learn more about using Classical Statistics as a potential data solution for your company >

See our Glossary of Data Science Terms for more examples of how data solutions can be applied to any industry.

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