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Showing posts with the label relative frequency

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Updated example of using baby names to illustrate bimodal distributions.

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...

Organizations sharing data in a way that is very accessible

A few weeks ago, I posted about how you can share data in such a terrible way that one is not breaking the law, but the data is completely unusable. This makes me think of all the times I am irked when someone states a problem but doesn't offer a solution to the problem. Instead, they just talk about what is wrong and not how it could be. So, as a counter piece, let's cheer on organizations that ARE sharing data in a way that is readily accessible. You could use this in class as a palate cleanser if you teach your students about data obfuscation. You could also use it as a way of helping your students understand how data really is everywhere. Or even challenge them to brainstorm an app that uses readily accessible data in a new way to help folks.  Pro-Publica This website lets you check how often salmonella is found at different chicken processing plants. All you need to do is enter the p-number, company, or location listed on your package of chicken: https://projects.propubli...

r/faux_pseudo's "Distribution of particles by size from a Cracker Jack box

I love my fellow Reddit data geeks over at r/dataisbeautiful . Redditor faux_pseudo created a frequency chart of the deliciousness found in a box of Cracker Jacks. I think it would be funny to ask students to discuss why this graph is misleading (since the units are of different size and the pop corn is divided into three columns). You could also discuss why a relative frequency chart might provide a better description. Finally, you could also replicate this in class with Cracker Jacks (one box is an insufficient n-size, after all) or try it using individual servings of Trail Mix or Chex Mix or order to recreate this with a smaller, more manageable sample size. Also, as always, Reddit delivers in the Comments section: