Matrix Deviations

Matrix deviations refer to the differences between actual data values and expected or reference values within a matrix (a grid of numbers). In data analysis, they help identify how much observed data deviates from a standard or predicted pattern. For example, in quality control, matrix deviations highlight areas where a product's measurements differ from standards, indicating potential issues. They are useful for understanding variability, detecting anomalies, and improving processes by pinpointing where data patterns diverge from expectations.