These stilted bear figures and their voices are sufficiently obnoxious in their own right, even without the tedious lampooning of p-values and the feigned horror at learning they should not be reported as posterior probabilities. Coincidentally, I have been sent several different p-value U-Tube clips in the past two weeks, rehearsing essentially the same interpretive issues, but this one (“what the p-value”*) was created by some freebee outfit that will apparently set their irritating cartoon bear voices to your very own dialogue (I don’t know the website or outfit.)
The presumption is that somehow there would be no questions or confusion of interpretation were the output in the form of a posterior probability. The problem of indicating the extent of discrepancies that are/are not warranted by a given p-value is genuine but easy enough to solve**. What I never understand is why it is presupposed that the most natural and unequivocal way to interpret and communicate evidence (in this case, leading to low p-values) is by means of a (posterior) probability assignment, when it seems clear that the more relevant question the testy-voiced (“just wait a tick”) bear would put to the know-it-all bear would be: how often would this method erroneously declare a genuine discrepancy? A corresponding “Bayesian bear” video practically writes itself, but I’ll let you watch this first. Share any narrative lines that come to mind.
*Reference: Blume, J. and J. F. Peipert (2003). “What your statistician never told you about P-values.” J Am Assoc Gynecol Laparosc 10(4): 439-444.
**See for example, Mayo & Spanos (2011) ERROR STATISTICS
Error Statistics Philosophy 
Here’s the website link: http://www.xtranormal.com/ The bears will be disappointed to learn that there is less to their posteriors than meets the eye, but it is a lesson they have coming.
Nathan: Indeed they do! Thanks for the link!
Since Jeffrey Blume is a likelihoodist and a protégé of Richard Royall, perhaps a Likelihood Bear rejoinder would be more appropriate.
Tangentially, this video always makes me laugh, especially the infodump at 2:10. It’s supposed to sound like gibberish to a statistician, but I have a background in biochemistry so it actually makes sense to me.
Corey. Yes I like the cartoon. It reminds me of the joke about the three scientists marooned on a desert island with a can of pineapple and no means to open it. “Place it in salt water” says the chemist “and wait for it to corrode”. “Takes too long,” says the physicist “and will taste awful. Place it on a fire and wait for it to explode.” “Too dangerous, the bits will be hard to find and they will be covered with sand,” says the mathematician. “OK what’s your solution?” say the other two. “Assume we have a can-opener”. ….And now the relevance to the cartoon. Then they notice there is a fourth present, a statistician. “Can you help?” “No. You should have consulted me when you designed the can.”
Stephen: I told the Bayesian variant* of this once to economists, and they convinced me that the joke actually originates in Econ, but I don’t recall what the economist pipes up with…
*i.e., “assume we have a can-opener”
Corey: Thanks. You always seem to know the sources of things. I see what you mean about the other video too.
I meant to note, the likelihoodist can say less, stuck as he is with outputting a comparative likelihood ratio.