Prescriptive Statistics

Service Description

Definition: Prescriptive statistics is not a formally recognized branch of statistics in the same way as descriptive or inferential statistics, but the term can be used informally to describe the use of statistical results to recommend actions. It focuses on interpreting statistical outcomes to prescribe or suggest what should be done based on data patterns, probabilities, and constraints. Purpose: To use statistical evidence—like regression coefficients, hypothesis tests, and probability distributions—to inform or justify decision options. It’s essentially the “what should we do based on the data’s findings?” aspect of statistical interpretation. Tools & Methods: Optimization models using statistical results Decision trees with probability weighting Regression-based decision thresholds Bayesian decision theory Example: Using statistical analysis of past quality data to determine optimal process settings that minimize defects, based on proven statistical relationships.