Yeah but you can’t really do that with a map. In a table you could. A report would likely report both, but also differentiate groups because you don’t usually want to report skewed data without explaining why.
I bet if go down to county or city level, you‘ll find differently colored areas such as cities relying on old steel, coal, textile economies. At least here in Germany I know areas where many people left their home areas in the 90ies. But that’s probably a geography lesson.
Yup! And if you have the right dashboard you can usually drill down by location down to that level and even include those additional factors as an overlay. I used to do that using census and labor statistics data, and it is indeed very cool.
I like using both. An average of say 300 miles with a median of 5 miles would show you that there is significant bias toward the lower end.
I’m not a statistician but that’s my understanding of the two metrics
Yeah but you can’t really do that with a map. In a table you could. A report would likely report both, but also differentiate groups because you don’t usually want to report skewed data without explaining why.
I bet if go down to county or city level, you‘ll find differently colored areas such as cities relying on old steel, coal, textile economies. At least here in Germany I know areas where many people left their home areas in the 90ies. But that’s probably a geography lesson.
Yup! And if you have the right dashboard you can usually drill down by location down to that level and even include those additional factors as an overlay. I used to do that using census and labor statistics data, and it is indeed very cool.