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Showing posts with the label frequency table

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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...
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The Humble Nutrition Label

I am in a hotel lobby in Portland, OR. I am attended Society for the Teaching of Psychology's Annual Conference on Teaching. I did a talk with my friend Jenny Kunz on syllabus redesign. We found that incorporating graphic design principles in syllabi improve retention of syllabus information.   Anyway, that reminded me of the recent passing of Burkey Belser. Who is that? He is the graphic designer who created the the labels on each and every food item sold in America. I learned about his passing from this remembrance in NPR. IT IS A FREQUENCY TABLE, Y'ALL. I never thought about it this way until, like, a week ago. After seeing these and using these for years and years. Okay, first, let's just take a moment to admire one of Belser's professional head shots. RIGHT?! Anyway, I had never heard of  Belser until I came across this remembrance on NPR: How to use in class: 1. Frequency table example. 2.Sometimes, I like to remind my students that the examples I have for them in...
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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:
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Pew Research's "Global views on morality"

Pew Research went around the globe and asked folks in 40 different countries if a variety of different behaviors qualified as "Unacceptable", "Acceptable", or "Not a moral issue". See below for a broad summary of the findings. Summary of international morality data from Pew The data on this website is highly interactive...you can break down the data by specific behavior, by country, and also look at different regions of the world. This data is a good demonstration of why graphs are useful and engaging when presenting data to an audience. Here is a summary of the data from Pew.  It nicely describes global trends (extramarital affairs are largely viewed as unacceptable, and contraception is widely viewed as acceptable). How you could use this in class. 1) Comparison of different countries and beliefs about what is right, and what is wrong. Good for discussions about multiculturalism, social norms, normative behaviors, the influence of religion ...
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