Types of Distributions Used in Six Sigma

This article discusses the common probability types of distributions in Six Sigma Black Belt Projects. Many statistical approaches you’ll learn later are built on the assumption that the data is normally distributed. So, it’s important to gain an early understanding of the normal distribution. We’ll also cover some less common statistical distributions used in Six Sigma Black Belt Projects and show why they matter.

The Normal Distribution

The most common distribution used in Six Sigma is the normal distribution.

The Normal Distribution has these 3 unique characteristics:

1. Only Random Error is Present
2. There is no evidence of Assignable Cause
3. There are no drifts or shifts in the data as evidenced by the fact that the [Mean = Median = Mode].

The obvious conclusion from items 1-3 is that if the data is not normally distributed, then the following are likely true:

1. Probably more than random error is present
2. Probably there is evidence of assignable special cause

Most Used and Abused Distribution

While pretty and smooth, the normal distribution is the most used probability distribution – and because it’s so misunderstood, it’s also the most abused. And while it serves as the foundation of many statistical tools that we’ll learn later in the Measure Phase and in the Analyze Phase, encountering the normal distribution in real life is not common.

Characteristics of Normal Distribution

The Normal Distribution is a function of two parameters: The Mean and the Standard Deviation.

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