Thats a great question Megan and I know I often give the before we had
computers argument and its not that satisfying. And I agree that we
shouldnt just see them as an alternative when theory-based methods dont
work, but as a reasonable approach on their own with large and small sample
sizes. But you can say they are still what is predominantly done in practice
and you can still talk about test statistics as giving additional
information beyond the p-value. Because I still tend to do fairly
traditional confidence intervals, then the theory-based p-value and test
statistic give me a nice transition there (though I often talk more in terms
of 2SEs in both cases and dont worry too much about the exact
multiplier/critical value). I think I would be pretty happy teaching a
course (like the CATALST folks do) that does very little with the
theory-based methods, but I dont think my client departments would be very
happy with me yet. Mostly I want students to understand what the p-value
and confidence interval mean and then turn things over to a computer (and to
be honest maybe not always know the exact details of what the computer is
doing) to get the output and focus on the conclusions we can draw
It is nice to show them two different reasonable approaches to help contrast
them. In fact, maybe we should be doing more with exact methods in place of
both of these?
Beth
From: sbi-bounces(a)causeweb.org [mailto:sbi-bounces@causeweb.org] On Behalf
Of Olson Hunt, Megan
Sent: Friday, January 02, 2015 11:13 AM
To: 'sbi(a)causeweb.org'
Subject: [SBI] Explaining motivation for theory-based models
Im working on transitioning our undergrad introductory statistics course to
one that involves simulation-based ideas alongside parametric, theory-based
models. At the risk of sounding naïve, I would like your opinion on the
following: With the advent of computers that make simulation-based p-value
calculations fast and easy, and for those of you that teach this idea in
parallel with theory-based p-values, how do you explain the motivation for
even using theory-based p-values to your students?
In other words, parametric models require assumptions that may not be met.
If we can use simulation to obtain a reliable p-value without worrying about
these assumptions, then why bother with a t-test (e.g.) for a p-value at
all? It seems like a historical argument (Its been done and probably will
continue to be done for quite some time) is one, but
Im left feeling like
I have to tell my students to conduct these theory-based tests just
because.
Thanks for your thoughts.
Megan