Learning statistics is difficult enough; throw in some especially confusing terminology and it can feel impossible! There are many ways that statistical language can be confusing.
Some terms mean one thing in the English language, but have another (usually more specific) meaning in statistics. (more…)
Multicollinearity is one of those terms in statistics that is often defined in one of two ways:
1. Very mathematical terms that make no sense — I mean, what is a linear combination anyway?
2. Completely oversimplified in order to avoid the mathematical terms — it’s a high correlation, right?
So what is it really? In English?
What is a Confounder?
Confounder (also called confounding variable) is one of those statistical terms that confuses a lot of people. Not because it represents a confusing concept, but because of how it’s used.
(Well, it’s a bit of a confusing concept, but that’s not the worst part).
It has slightly different meanings to different types of researchers. The definition is essentially the same, but the research context can have specific implications for how that definition plays out.
If the person you’re talking to has a different understanding of what it means, you’re going to have a confusing conversation.
Let’s take a look at some examples to unpack this.