The bell curve- just think 90% of the data is between -3sigma to +3sigma from the middle of the bell. Highly unusual to have data start to appear at the outer ends of the curve that should be close to zero.

A 10 sigma event is a statistical calculation that has data over ten standard deviations from a mean in a normal distribution. 3 sigma events are rare, 10 sigma events would be astronomically rare.

What is three sigma in statistics?

Three sigma in statistics is a calculation that has data in three standard deviations from a mean. Also referred to as the three sigma limits or empirical rule, this tool helps calculate the probability of a set of data. Three sigma follows the 68-95-99.7 rule, with 68% of the data within one standard deviation of the mean, 95% of the data within two standard deviations of the mean and 99.7% of the data within three standard deviations of the mean.

Related: 50 Statistics Terms To Know (With Definitions)

Three sigma vs. six sigma

Here are some differences between three sigma and six sigma:

Accuracy

Since six sigma calculates six standard deviations from the mean, its value tends to be more accurate than three sigma. A six sigma calculation has a 99.99966% accuracy, whereas a three sigma calculation has a 99.73% accuracy.

While the difference between these two calculations is less than 0.25% this area of error can have large affects on certain industries, such as manufacturing, banking and computers, where accuracy is vital. When reviewing data for those types of industries, professionals may choose to calculate six sigma rather than three sigma, since it reduces the margin of error.

Number of steps

Six sigma involves more steps than three sigma. This is because it calculates three additional standard deviations than three sigma.

Since six sigma involves more steps, there are more chances for errors to occur during calculations. However, when calculated correctly, it provides a more accurate dataset.