Smart's "The differences in how CNN MSNBC & FOX cover the news"

https://pudding.cool/2018/01/chyrons/

This example doesn't demonstrate a specific statistical test. Instead, it demonstrate how data can be used to answer a hotly contested question: Are certain media outlets biased?

How can we answer this? Charlie Smart, working for The Pudding, addressed this question via content analysis. Here is how he did it:

And here are some of their findings:

Yes, Fox News was talking about the Clintons a lot.

While over at MSNBC, they discussed the investigation into Russia and the 2016 elections ore frequently.

While kneeling during the anthem was featured on all networks, it was featured most frequently on Fox

And context matters. What words are associated with "dossier"?

How do the different networks contextualize President Trump's tweets?

Another reason I like this example: It points out the trends for the three big networks. So, we aren't a bunch of Marxist professors ragging on FOX, and we aren't a bunch of Fake Newsers ragging on MSNBC: We can dispassionately look at the trends present across the spectrum. I think this is important in diverse classrooms with diverse opinions.

I think this example also shows some really good visualizations for different sorts of data, allowing users to easily comprehend trend across time, comparisons among the three networks, etc.

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/

Search This Blog