John Oliver's "Scientific Studies" with discussion quesions

This hilarious video is making the rounds on the Interwebz. Kudos to John Oliver and his writing team for so succinctly and hilariously summarizing many different research problems...why replication is important but not rewarded, how research is presented to the public, how researchers over-reach about their own findings, etc. I Tweeted about this, but am making it cannon by sharing as a blog post.

Note: This video has some off-color humor (multiple references to bear fellatio) so it is best suited to college aged students.

I will use this in my Online and Honors classes as discussion prompts. Here are some of the prompts I came up with:

1) In your own words, why aren't replications published? How do you think the scientific community could correct this problem?

2) In your own words, explain just ONE of how a RESEARCHER can manipulate their own data and/or research findings. It should be one of the methods of manipulation described in the video. Also, don't just name the method of manipulation; explain it like you would explain it to a friend so that they could become aware of the issue AND know how to spot the problem.

3) Given what you have learned in this video AND your own experiences, who/what do you think is the most to blame for spreading bad science?

4) Given your response to item 3, describe one way to correct for this problem of misinterpreted data being shared inappropriately.

5) Why are replications necessary?

6) What major shortcoming of the "champagne" study was glossed over by the media? What major shortcoming of the "chocolate/pregnancy" study was glossed over? What is the difference between how study authors handle the limitations of their work versus how the media handles shortcomings in their work?

7) What were the red flags from the "hydration" study. Which do you consider to be the most damning and why?

BONUS POINT: Come up with a catchy pick-up line using the spotty Oxytocin research described in the clip.

Additionally, here is another one of my blog post (with links to other posts) related to the topic of scientific reporting.

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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