Applied statistics has a terminology problem. Four kinds of them, actually.

We have technical terms that mean something different than their everyday meanings, like significance. We have both single terms with multiple meanings (factor) and multiple terms with the same meaning, (mixed and multilevel models). And finally, there are terms that are so similar they’re easy to mix up, though they have distinct meanings.

The four kinds of terminology mishaps have two frustrating effects. They make communication especially hard when collaborators understand a term differently than you do. And they make statistics harder to learn when software, books, and articles are inconsistent in their terminology.

Join us to review and untangle many of these confusing terms. It will help you understand what your collaborators were talking about, and it will help you bring together seemingly different concepts so they make more sense.