Varianza

According to McClave, Benson, and Sincich (2011), measures of central tendency provide only a partial description of a quantitative data set. The description is incomplete without a measure of thevariability, or spread, of the data set. Knowledge of the data’s variability along with its center can help us visualize the shape of a data set as well as its extreme values.
Manufacturing andmeasurement processes exhibit variation where these measures come in handy. Dimensions, properties, or conditions may vary within certain practical limits without significantly affecting functioning ofequipment or a process. Tolerances are specified to allow reasonable margin for imperfections and inherent variability without compromising performance.
In the manufacturing business a variation beyondthe tolerance is said to be non-compliant, rejected, or exceeding the tolerance (regardless of whether this breach was of the lower or the upper bound). If the tolerance is set too restrictive it willresult in most objects run by it being rejected, it is said to be intolerant. At work we buy apparel stock lots and one of the reasons for these irregulars or “second quality” lots to be rejected byoriginal buyers is because the size specs are off the tolerance.
A knife manufacturer for example will benefit from these measures because the cost of the metal is a significant part of the coststructure, and rolling down to the minimum thickness that meets the customer specification can be the difference between profit and loss.
Most manufacturers would rate product quality as a key driver oftheir overall ability to satisfy customers and compete in a global market. While many companies still think of quality as “being in specification,” progressive companies focus on reducing variationto minimize waste and produce products that perform consistently well over time. Quality may be thought of as inversely proportional or in other words as variation increases, product quality...