Granqvist's "Why Science Needs to Publish Negative Results"

This link is worth it for these pictures alone:

I know, right? Perfect for teaching research methods and explaining the positivity bias in publication.

These figures also sum up the reasoning behind the new journal described in this article. New Negatives in Plant Science was founded in order to combat the file drawer problem. It publishes non-significant research. It is open access. It publishes commentaries. It even plans special issues for specific controversial topics within Plant Science. Which absolutely, positively are NOT my jam. However, the creators of this journal hope that it will serve as a model for other fields. Given the recent flare up in the Replication Crisis (now Replication War?), this new journal provides a model for on-going, peer reviewed, replication and debate.

I think this journal (or the idea behind this journal) could be used in a research methods class as a discussion piece. Specifically, how else could we reduce the file drawer problem? The Open Science Framework offers a new model for transparency in research. Retraction watch provides a highly visible platform for tracking research that makes it through peer review but is later pulled by a journal. What else could we be doing to better vet our research?

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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