We need more nonsignificant but readily understood examples in our classes. This correlation/regression example from Information is Beautiful  demonstrates that the calories in delicious caffeinated drinks do not correlate with the calories in the drink. Caffeine has zero calories. The things that make our drinks creamy and sweet may have calories. Easy peasy, readily understood, and this example gives your students a chance to think about and interpret non-significant, itty-bitty effect size findings.  Click here for the data. Aside: Watch your language when using this example. We need calories to stay alive and none of these drinks, in and of themselves, are good or bad. Our students are exposed to way too much of that sort of language and thinking about food and their bodies. What they choose to drink or eat is none of our business. When I share this visual, I omit the information on the far right (exercise) and far left (calorically equivalent foods). It distracts from the...

Not all of our class examples should reject the null. Sometimes, you just need some non-significant data, small effect size data that doesn't detect a linear relationship. Such is the linear relationship between the number of calories and mg of caffeine in these 29 different treats provided by InformationIsBeautiful. InformationIsBeautiful provides that data , as do I .

Twitter is my muse. This blog post was inspired by this Tweet:    In a study comparing blood concentrations of caffeine after coffee or energy drink consumption, blood caffeine levels peaked at about 60 minutes in all conditions. Plan accordingly. https://t.co/cWWakGGtHe pic.twitter.com/c5Nn3x3w1f — Kevin Bass (@kevinnbass) November 30, 2021 This study is straightforward to follow. I, personally, think it is psych-friendly because it is about how a drug affects the body. However, it doesn't require much psych theory knowledge to follow this example. Sometimes I'm worried that when we try too many theory-heavy examples in stats class, we're muddying the waters by expecting too much from baby statisticians who are also baby psychologists. Anyway. Here are some things you can draw out of this example: 1. Factors and levels in ANOVA The factor and levels are easy to identify for students. They can also relate to these examples. I wonder if they used Bang energy drinks? They a...

I am avoiding grading and trying to make this here blog more usable, so I am consolidating all of my funny scale examples into one location. Feast your eyes on this! https://earther.com/we-finally-know-what-hot-as-balls-really-means-1825713726 http://hyperboleandahalf.blogspot.com/2010/02/boyfriend-doesnt-have-ebola-probably.html http://notawfulandboring.blogspot.com/2018/01/this-is-very-silly-example-for.html

In honor of Daylight Savings Time and my own caffeine addiction. This will always be the funniest graph ever, p < .05. Property of Nathaniel James

A good way of demonstrating the power of illustrating data. And there is coffee. Dunkin' Donuts collected data about coffee drinking habits in the US. See below: Then, designer at en.ilovecoffee.jp turned this hum-drum data into very  p retty data : Property of en.ilovecoffee.jp