The thing about my way of teaching stats is that my cool, novel examples get old really fast. Like, pop culture is on a thirty-day cycle. Anyway, YEARS ago, 2014 to be exact, I blogged about illustrating bimodal data distributions using baby name data from the Social Security Administration. Specifically, when an older name comes back into vogue, it has a bimodal distribution when you plot time on the X axis. I stand by this example. However, all of the data illustrations come from 2014. When our traditionally aged college students were 6 or 7. Which makes this example feel a little stale. However, here is some data, courtesy of Redditor fevaah , showing old names that are back in vogue through 2025 ! And Eleanor, Violet, Nora, and Hazel are here, illustrating bimodal distributions for a new generation. If you used my old baby-name data, this is a quick, easy refresh for your lectures (or a fun new addition if you didn't). If this idea was help...
In my Honors Statistics class, we have days devoted to discussing thorny issues surround statistics. One of these days is dedicated to the disconnect between science and science reporting in popular media.
I have blogged about this issue before and use many of these blog posts to guide this discussion: This video by John Oliver is hilarious and touches on p-hacking in addition to more obvious problems in science reporting, this story from NPR demonstrates what happens when a university's PR department does a poor job of interpreting research results. The Chronicle covered this issue, using the example of mis-shared research claiming that smelling farts can cure cancer (a student favorite), and this piece describes a hoax that one "researcher" pulled in order to demonstrate how quickly the media will pick up and disseminate bad-but-pleasing research to the masses.
When my students and I discuss this, we usually try to brain storm about ways to fix this problem. Proposed solutions: Public shaming of bad journalists, better editing of news stories before they are published, a prestigious award system for accurate science writing. And another idea my students usually arrive upon? Better training for journalists.
So, you can imagine how pleased I was to discover that such classes already exist via Sense about Science USA.
Their mission:
They support this mission in a few different ways. They advocate for registering all medical trials conducted on humans. They are training scientists to more effectively communicate their findings to the public. And, apropos of this blog, they are also training journalists to better understand statistics AND offer one-on-one consulting to journalists trying to understand data.
Here is their description of why it is important to better train journalists.
How to use in class:
1) Instead of just showing students the problems associated with poor science writing, let's show them a possible solution as well.
2) Statistics isn't just for statisticians, statistics are for anyone who wants to better understand policy issues, emerging research, and evidence-based practices in their field.
3) Show your students some examples of poor science writing. Have them develop a brief presentation that would address the most common statistical mistakes made by science writers.
I have blogged about this issue before and use many of these blog posts to guide this discussion: This video by John Oliver is hilarious and touches on p-hacking in addition to more obvious problems in science reporting, this story from NPR demonstrates what happens when a university's PR department does a poor job of interpreting research results. The Chronicle covered this issue, using the example of mis-shared research claiming that smelling farts can cure cancer (a student favorite), and this piece describes a hoax that one "researcher" pulled in order to demonstrate how quickly the media will pick up and disseminate bad-but-pleasing research to the masses.
When my students and I discuss this, we usually try to brain storm about ways to fix this problem. Proposed solutions: Public shaming of bad journalists, better editing of news stories before they are published, a prestigious award system for accurate science writing. And another idea my students usually arrive upon? Better training for journalists.
 |
| http://www.senseaboutscienceusa.org/ |
So, you can imagine how pleased I was to discover that such classes already exist via Sense about Science USA.
Their mission:
They support this mission in a few different ways. They advocate for registering all medical trials conducted on humans. They are training scientists to more effectively communicate their findings to the public. And, apropos of this blog, they are also training journalists to better understand statistics AND offer one-on-one consulting to journalists trying to understand data.
Here is their description of why it is important to better train journalists.
 |
| http://www.senseaboutscienceusa.org/stats_workshops/ |
How to use in class:
1) Instead of just showing students the problems associated with poor science writing, let's show them a possible solution as well.
2) Statistics isn't just for statisticians, statistics are for anyone who wants to better understand policy issues, emerging research, and evidence-based practices in their field.
3) Show your students some examples of poor science writing. Have them develop a brief presentation that would address the most common statistical mistakes made by science writers.