Monday, November 20, 2017

Math With Bad Drawing's "Why Not to Trust Statistics"

Bad Math with Drawings has graced us with statistical funnies before (scroll down for the causality coefficient). Here is another one, a quick guide pointing out how easy it is to lie with descriptive statistics. Here are two of the examples, there are plenty more at Math With Bad Drawings.

Variance example
https://mathwithbaddrawings.com/2016/07/13/why-not-to-trust-statistics/
https://mathwithbaddrawings.com/2016/07/13/why-not-to-trust-statistics/



Monday, November 13, 2017

Using The Onion to teach t-tests

In the past, I've used fake data based on real research to create stats class examples. Baby names, NICUs, and paired t-test. Pain, surgical recovery, and ANOVA.

Today, I've decided to use fake data and fake research to create a real example for teaching one-sample t-test. It uses this research report from The Onion:

https://www.theonion.com/toddler-scientists-finally-determine-number-of-peas-tha-1820347088


In this press release, the baby scientists claim that the belief that a baby could only smash four peas into their ear canal were false. Based upon new research recommendations, that number has been revised to six. Which sure sounds like a one-sample t-test to me. Four is the mu assumed true based upon previous baby ear research. And the sample data had a mean of 6, and this was statistically significant.

Here is some dummy data that I created that replicates these findings, when mu/test value is set to 4. :

5.00
6.00
7.00
6.00
5.00
6.00
6.00
5.00
7.00
6.00
7.00

Why, yes, I do think I'm pretty clever.

Monday, November 6, 2017

Yau's Real Chart Rules to Follow

The sum of the parts is greater than the whole? Nathan Yau's article on creating readable, useful graphs  is a perfectly reasonable list of how to create a proper graph. The content is sound. So, that's good.

However, the accompanying images and captions are hilarious. They will show your students how to make not-awful charts.