Skip to main content

NY Magazine's "Finally, Here’s the Truth About Double Dipping"


Yes, it includes the Seinfeld clip about George double dipping.


The video provides a brief example of how to go about testing a research hypothesis by operationalizing a hypothesis, collecting, and analyzing data. Here, the abstract question is about how dirty it is to double dip. And they operationalized this question:


Research design: The researchers used a design that, conceptually, demonstrates ANOVA logic (the original article contains an ANOVA, the video itself makes no mention of ANOVA). The factor is "Dips" and there are three levels of the factor:




Before they double dipped, they took a base-line bacterial reading of each dip. Good science, that.
They display the findings in table form (again, no actual ANOVA). 

I am totally horrified by this salsa data.



However...the acidity of the salsa seems to help out in terms of killing bacteria after two hours. So, dig into that bowl of salsa two hours after your last guests go home? Still ew.

Because of the re-testing, using 1) baseline, 2) Time 1, and 3) Time 2, this now becomes a good example of a repeated measures ANOVA.


How to use in class:

1) How do we go from a research question to research?
2) ANOVA
3) Repeated measure design

Popular posts from this blog

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/