Monday, September 26, 2016

Hyperbole and a Half's "Boyfriend doesn't have ebola. Probably. "

I've been using this example in class for a few years but never got around to blogging about it until now.

It seems that the first chapter of every statistics class provides a boring explanation of what a variable is, and examples of variables, and operationalizing variables, and quantifying the abstract for the purposes of conducting statistical analyses.

I try to make that boring topic funnier and applicable to real life via this post entitled "Boyfriend doesn't have ebola. Probably." from Allie Brosh, editor of Hyperbole and a Half.

In this posting, she rips apart the good old FACES scale after a trip with her boyfriend to the ER.

Why does she rip apart the FACES scale? Because she does not think that it does an appropriate job of explaining just how painful the pain is when you are in the ER. This leads to her creating a new FACES scale that more appropriately conveys the level of distress one experiences at the ER. See below.

And if you are a proper psychometrician, you know that your Likert-type scale needs anchors. Here are the one's the author created:

Anyway, it is hilarious, she is hilarious.

How to use in class:

-Psychologists turn abstract ideas, like pain, into operationalized variables. See above.
-FACES is important not just in medical situations, but when conducting developmental psychology research.
-Is data collected via this scale nominal or ordinal or interval or ratio?
-You have a variable, a range of potential scores for the variable, and the scale of measurement.
-I teach many students who are studying to be PTs, OTs, PAs, and nurses. Throwing in the occasional medical example helps me reach those guys.
-Many of your students, regardless of major, have probably seen the FACES scale.

Monday, September 19, 2016

If your students get the joke, they get statistics.

Gleaned from multiple sources (FB, Pinterest, Twitter, none of these belong to me, etc.). Remember, if your students can explain why a stats funny is funny, they are demonstrating statistical knowledge. I like to ask students to explain the humor in such examples for extra credit points (see below for an example from my FA14 final exam).

Using for bonus points/assessing if students understand that correlation =/= causation

What are the numerical thresholds for probability? 

How does this refer to alpha? What type of error is being described, Type I or Type II?

What measure of central tendency is being described?

Sampling, CLT
Because control vs. sample, standard deviations, normal curves. Also,"skewed" pun. If you go to the original website, the story behind this cakes has to do with a section of crappy that is kind of funny and therapeutic for us teachers.

NOTE: The website the cake example comes from contains a lot of NSFW language. Which I, personally, have no problem with, but you might.
Because bar graphs, error bars, and understanding the joke behind this graph.
What kind of error, Type I or Type II?
 Reliability, n-size
What does correlation give us? What does it not?

What does the r^2 here indicate? Why would it be difficult to guess the direction of the relationship?

xkcd's Linear Regression

This comic is another great example of allowing your student to demonstrate statistical comprehension by explaining why a comic is funny. What does the r^2 indicate? When would it be easy to guess the direction of the correlation? More on that via this previous blog post.