There’s Something About Variance

There’s Something About Variance

Variability is inevitable but you can control some of it. There are times when the supply chain works effortlessly, and other times ... helps managers maintain their cool when something goes wrong.

Imagine practicing hitting a target using darts, a bow and arrow, pistol, cannon, missile launcher, or whatever. You aim for the center of the target. If your shots land where you aimed then you are considered to be accurate. If all your shots land near each other, you are considered to be precise. The two properties are not linked. You can be accurate but not precise, precise but not accurate, neither accurate nor precise, nor both accurate and precise.

Accuracy and precision also apply to statistics calculated from data. If you’re trying to determine some characteristic of a population (i.e., a population parameter), you want your statistical estimates of the characteristic to be both accurate and precise.

The same also applies to the data themselves. When you start measuring data for an analysis, you’ll notice that even under similar conditions, you can get dissimilar results. That lack of precision is called variability. Variability is everywhere; it’s a normal part of life. In fact, it is the spice in the soup. Without variability, all wines would taste the same. Every race would end in a tie. Even statistics might lose its charm. Your doctor wouldn’t tell you that you have about a year to live, or say don’t make any plans for January 11 after 6:13 pm EST. So a bit of variability isn’t such a bad thing. The important question, though, is what kind of variability?

statistics data-science variability precision variance

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