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Using “Standard Deviation” as a Measure of Data Spread or Dispersion
A measure of dispersion tells you the spread of the data. It is important to know the spread of your data when describing your data set. Most describe a set of data by using only the mean or median leaving out a description of the spread.
There are two main measures of spread or dispersion:
In this article we will discuss the Cumulative probability of a normal distribution with expecte... Learn More... of the Distribution
The standard deviation(s) is the most common measure of dispersion. Standard deviation tells you how spread out or dispersed the data is in the data set. It is a measure of how far each observed value in the data set is from the mean. In any distribution, theoretically 99.73% of values will be within +-3 standard deviations of the mean.
Why is Standard Deviation Important in Lean Six Sigma?
Let’s look at an example. Let’s say I owned a company that produced widgets as a sub-component for other parts. Every time a widget is produced, a system records the time it took from start to finish of the widget. The requirements for the time to complete a widget is no less than 6 minutes and no more than 18 minutes.
In the below example, we calculate the standard deviation as 1.5 minutes from a sample of 60 widgets.
What happens if the standard deviation increases? Let’s see:
These illustrations show that knowing the standard deviation and tolerance of a process can show the performance of the process. Knowing the performance of a process is critical in a Lean Six Sigma project.