Measurement error in intro stats

I have recently been asked by my doctor to closely monitor my blood pressure, and report it if it’s above a certain cutoff. Sometimes I end up reporting it by calling a nurse line, sometimes directly to a doctor in person. The reactions I get vary from “oh, it happens sometimes, just take it again in a bit” to “OMG the end of the world is coming!!!” (ok, I’m exaggerating, but you get the idea). This got me thinking: does the person I’m talking to understand measurement error? Which then got me thinking: I routinely teach intro stats courses that for some students is the only stats, and potentially only quantitative reasoning, course they might take in college, do I discuss measurement error properly in this course? I’m afraid the answer is no… It’s certainly mentioned within the context of a few case studies, but I can’t say that it gets the emphasis it deserves. I also browsed through a few intro stats books (including mine!) and not a mention of “measurement error” specifically.

I’m always hesitant to make statements like “we should teach this in intro stats” because I know most intro stats curriculum is already pretty bloated, and it’s not feasible to cover everything in one course. But this seems to be a pretty crucial concept for someone to understand in order to be able to have meaningful conversations with their health providers and make better decisions (or stay calm) about their health that I think it is indeed worth spending a little bit of time on.

2 thoughts on “Measurement error in intro stats

  1. I think this is a great idea. Blood pressure measurements are something that we all experience and I’ve had the same range of reactions as you describe. It would be nice to know what is realistic in terms of range of measurements within a day/hour/week/ month and how we might collectively use the information to determine whether there’s actually a problem or not!

  2. Isn’t that contained in the concept of sampling error? I mean, as long as one covers the CLT (or even just the LLN) in a intro stats course, then basically measurement error is well illustrated by the classic example of multiple measurements with a balance (or a dynamometer). One can consider the standard deviation known, to simplify things a bit.

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