Median: Six Sigma's Best Middle Man (#66)


Median: Six Sigma’s Best Middle Man

Reflecting back to fond memories (just kidding) of grade school math, you’ll remember that there are three basic values used to teach students about groups of numbers. In Six Sigma, we use these values to measure Central Tendency. These measurements are:

Mean; the sum of all the numbers in the data set divided by the amount of numbers represented.

Median; the very middle number of the data set (if there are two middle numbers, the median value would be the average of the two numbers).

Mode; the number most represented in the data set.

Today, I want to talk to you about Six Sigma’s Best Middle Man.

The simplicity of the Median value is just that, Median is the very center value in a group of data when said data is arranged in numerical order. If there are two Median Values (this happens in data sets of even numbers, i.e. when there are 12 data points, etc.) then you would average the two numbers. Check out some examples below.

Data Set #1

2, 3, 5, 6, 7, 9, 11, 14, 16, 17, 19, 20, 22: Median = 11

Data Set #2

2, 3, 5, 6, 7, 9, 11, 14, 16, 17, 19, 20, 22, 23: Median = ((11+14)/2) = 12.5



When a data set has been outlined, the Median is valued as the 50% mark. Normally, your Median will be equivalent or very close to the Mean of the data set. Also, your Mode value (the value that happens the most) will also be close to the Median and Mean value; in most situations. If a distribution is skewed one way or another, the defining values of Median and Mode will be skewed in the same direction. Check out the images below to see some examples of skewed data sets.











What if you have skewed data in your Lean Six Sigma Project?

Most often you will find skewed distributions when your data is a representative of time. I.E. a pizza delivery service measures the time it takes to deliver pizzas in town. This pizza delivery service is consistently working to decrease their “late delivery” times down to zero. This kind of data would show most data points clustered by/around/close to the zero value. This kind of data’s Central Tendency is best described by the Median Value.

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