This spicy example explains scales of measurement, continuous vs. categorical variables, and how you can measure and quantify anything.  Uncommon Goods sells quirky gifts. While I was looking for Christmas gifts last year, I came across this kit https://www.uncommongoods.com/product/scoville-scale-chili-pepper-tasting-kit#618780000000 I have a teenage son, and teen boys love this sort of stuff. Actually, I think spicy peppers are enjoying increased popularity due to the Hot Ones show (The show where celebrities eat increasingly hot chicken wings while being interviewed, like Jennifer Lawrence and her famous GIF from the show).  Maybe you could link this example back to that show? Welcome to how my brain works. Anyway, among the information Uncommon Goods shared about this kit was an image of the packaging for the kit, detailing the Scoville scale rating for each pepper: And my stats teacher brain translated this packaging into this, since the same data (hottness) is presented ...

As I write this, I am a parent on the first day of summer break, and I have two kids who are very different from one another. So, these hilarious examples of Type I/II error from Alison Horst really speaks to me.  Not only are these illustrations beautiful and funny, but I think they really get your students to think about one HUGE underlying issue in all of inferential statistics: Every little sample that we analyze is just one of near-infinite possible samples that could have been drawn from the underlying population (or, the sampling distribution of the sample mean). Head over to her GitHub for a funny, normal curve illustration and higher resolution versions of the above pictures. She also has numerous beautiful R and ggplot illustrations . UPDATE: 11/6/19 Alison made some super cute illustrations for a topic that is simultaneously very boring but also tricky for baby statisticians: Scales of measurement.