The first part of this article is very true: "... correlation doesn't always equal causality." It's a fun look at statistics and there's a short video from a news station that contains this other great quote: "... numbers can be tricky."

As data professionals, we are often tasked with helping business people understand the information hidden in data. We look to identify patterns and relationships between the data that our applications collect or our companies purchase. However it's not as simple as it might appear.

This week, I'm wondering if you have some fun stories, or perhaps some scary stories, on conclusions that you or others have reached with data.

When has a correlation been mistaken for causation by you?

I know that most people in business don't have extensive statistics backgrounds, and I've often seen people fooled by finding simple or obvious patterns in data that didn't necessarily match reality. I've seen plenty of money lost because of bad decisions made by incorrect data interpretations.

I once worked in a restaurant where a new chef decided to use sales data from the previous year to predict how many meals would be served. Using a growth factor from sales over the previous year, he increased his purchasing as the summer season approached. A month into summer, we realized that we were wasting almost twice as much food as we had in the past. I had a similar story where purchasing managers used a straight average of the previous three months that left is woefully short on imported wood.

Let us know this week if you've seen mistakes made from naive interpretations of statistics.