NPR's The Pandemic Is Pushing Scientists To Rethink How They Read Research Papers

This NPR story by Richard Harris describes science's struggle to keep up with the massive amount of COVID-19 research, much of which is coming out of China. How does science, and society, judge the quality of these papers?

How to use in class:

1. How do scientists assess the quality of research? By reading pre-registered reports and pre-prints: The report explains pre-prints and pre-registration! The good: The research gets out faster. Reviewers can compare pre-planned analysis to the actual analysis. The bad: The media gets too excited about pre-prints.

The report describes the totally overwhelming number of pre-prints for COVID-19 related research:

One of the scientists interviewed in the piece describes how he used pre-registered information to assess a COVID-19 research paper:

Screen shot from the NPR story: https://www.npr.org/sections/health-shots/2020/07/07/884957449/the-pandemic-is-pushing-scientists-to-rethink-how-they-read-research-papers

2. How do scientists assess the quality of an article: By the author and their academic affiliation. The report describes the bias that may exist when we lean on author/affiliation heuristics in assessing science.

3. Science needs world-wide collaborations, and America needs foreign-born scientists. One scientist describes how international collaborations are sometimes built up post-docs from foreign countries working in the United States. Given the unstable situation in America regarding international students and work visas, this is especially pertinent. Such policies aren't just biased and isolating, they slow down innovation.

4. All of the lessons our students are learning from their psychology professors about how science works in psychology apply outside of psychology as well! This may be obvious to a person with a Ph.D. in psychology. However, I don't think that our students always realize this. Emphasizing this point is important for helping build their science literacy.

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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