Six Sigma is data-driven. Six Sigma statistics play an important role in Six Sigma’s problem-solving process. Six Sigma Green Belt training emphasizes the importance of Six Sigma statistics to visualize, analyze, and control the data for each metric that is important to customers. Six Sigma statistics can be applied in different ways in Six Sigma projects. Six Sigma training is free. Let’s take a look at the Six Sigma statistics at the heart and soul of the Six Sigma process.

Six Sigma Statistics Standard Deviation Rule

Let’s now recall the empirical rule that Six Sigma statistics have for standard deviation. This figure illustrates an extension of the same rule.

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The rule is:

68% of data points will be within +- 1 standard deviation from the average

95% of observations will fall within +-2 standard deviations of the mean

99.73% will be within +- 3 standard deviations of the mean

For Six Sigma statistics, the extension would be as below:

99.9937% will be within +- 4 standard deviations of the mean

99.99994% will be within +- 5 standard deviations of the mean

99.9999998% percent of data points fall within +-6 standard deviations from mean

Six Sigma statistics state that 99.9999998% must be within six standard deviations of the mean in order to qualify as Six Sigma projects. This means that only 0.0000002% can be outside the expected results. This is how Six Sigma statistics can be used to improve the quality of projects.

Limitations on Specification

These standard deviations are found on both the left tails and right tails of Six Sigma statistics. Six Sigma statistics states that there will be both higher and lower values than the mean in any given process. It is essential that a limit be set for a particular metric in order to produce quality products.

There are two types specification limits. The lower specification limit, also known as LSL, is the lowest acceptable limit that a customer can set. The second is the upper specification limit. This is the maximum acceptable limit as determined by a customer. These limits are usually set by the customer. This is why USL – LSL = Voice of the Customer

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Let’s look at a sample graph to better understand Six Sigma statistics. The range, variance and standard deviation are the measures of the Six Sigma process spread. These are the most important Six Sigma statistics terms. Based on the dispersion data, the specification spread (USL-LSL) divided by 6s is called “Short-term process Capability”. The greater the process capability, the further the specification spreads from the process spread. In other words, the greater the process capability, the less variation.

Defects and Defectives

Let’s look at the differences between Defectives and Defectives. Defects are when a product or service is not delivered as promised. Defective refers to the failure of the entire product/service. It is possible for one product to have multiple defects, but that does not necessarily make it defective. Six Sigma statistics is used for determining the extent of defects and defectives.

We all know that the center of a process can be measured in three ways: median, mode, and mean. These parameters are critical in Six Sigma statistics. In ca