It is important in the practice of statistics, Six Sigma projects, and analysis of data. First understand the central tendency of your data as does the data tend to be a symmetrical bell curve shape once you put it into the form of a histogram? or Is it severely skewed left or right?
From there, you want to understand the dispersion.
- How far does the data stray from the central point that you’re looking for?
- How far out to the left or right?
- You also need to know, within one standard deviation, how much dispersion is in there that would take in 66 to 67% of the entire data population for your project.
You can see some characteristics of dispersion when you compare two example histograms. The histograms display the different call handle times for a technical support center. They have approximately the same mean value but the second histogram has a greater range than the first one. You could have essentially the same number of observations and maybe even the same mean value at the center, but you could have a big difference in the dispersion between them.
There are three important measures of dispersion:
- standard deviation, which measures the amount of dispersion from the average, left or right, from the center value in your data
- range, which is essentially the spread of the data, or how far to the left and to the right of your central measurement it goes
- variance, which is the square of the standard deviation and characterizes the difference between the individual measurements in the entire study
