Data purists would rap my knuckles for asking this question and reply, "Never". On the other hand, "data sophists" who're accustomed to lying with Big Data in even more crude ways would wonder, “Duh, ...

I often teach in my statistics class that correlation should not be confused with causation. That is, observing that two variables move together does not necessarily mean that one variable caused the ...

In traditional decision making, the metrics that impact the bottom line will almost always take precedence over the underlying drivers of change. The reasons behind a purchase decision fade into ...

Correctly distinguishing between correlation and causation is critical because it influences how treatments for illnesses are devised and tested. Also, in the context of the law, it ensures that as ...

Most studies include multiple response variables, and the dependencies among them are often of great interest. For example, we may wish to know whether the levels of mRNA and the matching protein vary ...

With the explosion of interest in Big Data everyone in every department is looking for actionable intelligence. That’s great but there’s a downside: Trying to explain to, say, your VP of sales that ...

There’s an old saying that goes, “figures don’t lie, but liars can figure.” But sometimes even the figures can spin a confusing story. That’s why I’ve always appreciated the power of understanding ...