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A three sigma limit is a statistical calculation in which the data are within three standard deviations from a mean. Three sigma refers to processes in business applications that operate efficiently and produce items of the highest quality.
Three sigma limits are used to set the upper and lower control limits in statistical quality control charts. Control charts establish limits for a manufacturing or business process that's in a state of statistical control.
Control charts are also known as Shewhart charts, named after Walter A. Shewhart, an American physicist, engineer, and statistician (1891–1967). Control charts are based on the theory that a certain amount of variability in output measurements is inherent even in perfectly designed processes.
Control charts determine if there's a controlled or uncontrolled variation in a process. Variations in process quality due to random causes are said to be in control. Out-of-control processes include both random and special causes of variation. Control charts are intended to determine the presence of special causes.
Statisticians and analysts use a metric known as the standard deviation to measure variations, also referred to as sigma. It's a statistical measurement of variability showing how much variation exists from a statistical average.
Sigma measures how far observed data deviates from the mean or average. Investors use standard deviation to gauge expected volatility.
Consider the normal bell curve which has a normal distribution. The farther to the right or left a data point is recorded, the higher or lower the data is than the mean. Low values indicate that the data points fall close to the mean. High values indicate that the data is widespread and not close to the average.
Let’s consider a manufacturing firm that runs a series of 10 tests to determine whether there's a variation in the quality of its products. The data points for the 10 tests are 8.4, 8.5, 9.1, 9.3, 9.4, 9.5, 9.7, 9.7, 9.9, and 9.9.
Three sigma limits set a range for the process parameter at 0.27% control limits. Three sigma control limits are used to check data from a process and to determine if it's within statistical control by checking if data points are within three standard deviations from the mean. The upper control limit (UCL) is set three sigma levels above the mean and the lower control limit (LCL) is set at three sigma levels below the mean.
Standard deviation is a statistical measurement. It calculates the spread of a set of values against their average. It's the positive square root of the variance and defines the difference between the variation and the mean.
A bell curve gets its name from its appearance: a bell-shaped curve that rises in the middle. It illustrates normal probability and several graphs and distributions use it. The single line measures data on one, two, and three standard deviations.
The term "three sigma" points to three standard deviations. Shewhart set three standard deviation (3-sigma) limits as a rational and economic guide to minimum economic loss.
Around 99.73% of a controlled process will occur within plus or minus three sigmas so the data from a process ought to approximate a general distribution around the mean and within the predefined limits. Data that lie above the average and beyond the three sigma line on a bell curve represent less than 1% of all data points.
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