Dirty Data: Share the data in a way that is functionally inaccessible

In my intro stats class, we discuss shady data practices that aren't lying because they report actual numbers. But they are still shady because good data is presented in such a way as to be misleading or confusing.

These topics include:

Truncating the y-axis

Collecting measures of central tendency under ideal circumstances

Manipulate online ratings (I didn't write the blog post about this yet, but it is coming).

Relative vs. Absolute Risk

AND HERE IS ANOTHER ONE:

Insurance companies were asked to provide price data RE: the Transparency in Coverage Rule in the Consolidatedated Appropriations Act of 2021. Google that if you want to know more about that, I'm not going into that. Not my lane. That said, it is an appealing idea. Let's have some transparency in our jacked-up healthcare system.

And the insurance companies provided the data, but in a way inaccessible to most people. Like, all people, maybe? Because they just splurted out 100 TB of data. So, they totally complied with the law. But they were Shady.

The problem, and a possible solution, are detailed in this blog post from Alex Stein.

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr. Molly Metz maintains a curated list of hilarious "How you doing?" scales. 2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables. So, I decided to create a post about three ways to use these scales in your stats classes: 1) Teaching the basics of variables. 2) Nominal vs. ordinal scales. 3) Daily check-in with your students. 1. Teach your students the basics...

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing, I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.

Tyler Vigen's Spurious Correlations

Tyler Vigen has has created a long list of easy-to-paste-into-a-powerpoint graphs that illustrate that correlation does not equal causation. For instance, while per capita consumption of cheese and number of people who die by become tangled in their bed sheets may have a strong relationship (r = 0.947091), no one is saying that cheese consumption leads to bed sheet-related death. Although, you could pose The Third Variable question to your students for some of these relationships). Property of Tyler Vigens, http://i.imgur.com/OfQYQW8.png Vigen has also provided a menu of frequently used variables (deaths by tripping, sunlight by state) to help you look for specific examples. This portion is interactive, as you and your students can generate your own graphs. Below, I generated a graph of marriage rates in Pennsylvania and consumption of high fructose corn syrup. Generated at http://www.tylervigen.com/

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