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Showing posts with the label covariate

Seven mini-stats lessons, crammed into nine minutes.

 I found this Tweet, which leads to a brief report on BBC. A recent report from the World Obesity Federation shows COVID death rates are higher in countries where more than half the population is overweight. Cause and effect, or bad statistics? @TimHarford and @d_spiegel explore - with some maths from me. You can listen on @BBCSounds https://t.co/hevepmz8RC — stuart mcdonald (@ActuaryByDay) March 14, 2021 The BBC has a show called "More or Less," and they explained a recent research finding connecting obesity to COVID 19 deaths.  Here is the original research study . Here is a pop treatment of the original study . For more stats news, you can follow  "More or Less" on Twitter . And they cram, like, a half dozen lessons in this story. It is amazing. I've tried to highlight some of the topics touched upon in this story. How can you use it in class? I think it would be a good final exam question. You could have your students listen to the story, and highlight ...

Everything is fucked: The syllabus, by Sanjay Srivastava (with links to articles)

This syllabus for  PSY 607: Everything is Fucked ,  made the rounds last week. The syllabus is for a course that  purports  that science is fucked. The course readings are a list of articles and books that hit on the limitations of statistics and research psychology ( p -values, shortcomings of meta-analysis, misuse of mediation, replication crisis, etc.). PSY 607 isn't an actual class ( as author/psychologist/blogger Srivastava explains in this piece from The Chronicle ) but it does provide a fine reading list for understanding some of the current debates and changes in statistics and psychology.  Most of articles are probably too advanced for undergraduates but perfectly appropriate for teaching graduat e students about our field and staying up to date as instructors of statistics. Here is a link to the original blog post/syllabus. 

Harris' "How Big A Risk Is Acetaminophen During Pregnancy?"

This study, which found a link between maternal Tylenol usage during pregnancy and ADHD, has been making the rounds, particularly in the Academic Mama circles I move in. Being pregnant is hard. For just about every malady, the only solution is to stay hydrated. With a compromised bladder. But at least pregnant women have Tylenol for sore hips and bad backs. For a long time, this has been the only safe OTC pain reliever available to pregnant women. But a recent research article has cast doubt on this advice. A quick read of this article makes it sound like you are cursing your child with a lifetime of ADHD if you take Tylenol. A nd this article has become click-bait fodder. But these findings have some pretty big caveats.  Harris published this reaction piece at NPR . It is a good teaching example of media hype vs. incremental scientific progress and the third (or fourth or fifth) variable problem. It also touches on absolute vs. relative risk. NOTE: There are well-documente...

Shapiro's "New Study Links Widening Income Gap With Life Expectancy"

This story is pretty easy to follow. Life expectancy varies by income level . The story becomes a good example for a statistics class because in the interview, the researcher describes a multivariate model. One in which multiple different independent variables (drug use, medical insurance, smoking, income, etc.) could be used to explain the disparity the exists in lifespan between people with different incomes. As such, this story could be used as an example of multivariate regression. And The Third Variable Problem. And why correlation isn't enough. In particular, this part of the interview (between interviewer Ari Shapiro and researcher Gary Burtless) refers to the underlying data as well as the Third Variable Problem as well as the amount to variability that can be assigned to the independent variables he lists). SHAPIRO: Why is this gap growing so quickly between life expectancy of rich and poor people? BURTLESS: We don't know. More affluent Americans tend to engage...

Oster's "Everybody Calm Down About Breastfeeding"

I just had a baby. Arthur Francis joined our family last week. Don't mind the IV line on his head, he is a happy, chubby little boy. Now, I am the mother of a new born and a toddler. And I have certainly been inundated by the formula versus breast feeding debate. In case you've missed out on this, the debate centers around piles and piles of data that indicate that breast fed babies enjoy a wealth of developmental outcomes denied to their formula fed peers. Which means there is a lot of pressure to breast feed (and some women feel a lot of guilt when they can't/do not want to breast feed). However, the data that supports breast feeding also finds that breast feeding is much more common among  educated, wealthy white women with high IQs. And being born to such a woman probably affords a wealth of socioeconomic advantages beyond simply breast milk. These issues, as well as mixed research findings, are reviewed in Emily Oster's "Everybody calm down about brea...

NFL.com's Football Freakanomics

EDIT: All of this content appears to have been removed from NFL.com. If anyone has any luck finding it, please email me at hartnett004@gannon.edu The NFL and the statistics folks over at Freakonomics got together and made some...learning modules? Let's call them learning modules. They are interactive websites that teach users about very specific questions related to football (like home field advantage , instances when football player statistics don't tell the whole story about a player/team , whether or not firing a head coach improves a failing team , the effects of player injury on team success , etc.) and then answer these questions via statistics. Most of the modules include interactive tables, data, and videos (featuring the authors of Freakanomics) in order to delve into the issue at hand. For example: The Home Field Advantage : This module features a video, as well as a interesting interactive map that illustrates data about the exact sleep lost experienced by ...

Emily Oster's "Don't take your vitamins"

My favorite data is data that is both counter-intuitive and tests the efficacy of commonly held beliefs. Emily Oster's (writing for 538) presents such  data in her investigation of vitamin efficacy . The short version of this article: Data that associates vitamins with health gains are based on crap observational research. More recent and better research throws lots of shade on vitamin usage. Specific highlights that could make for good class discussion: -This article explains the flaws in observational research as well as an example of how to do good observational research well (via The Physician's Health Study , with large samples of demographically similar individuals as described in the portion of the article featuring the Vitamin E study). This point provides an example of why controlled, double-blind lab research is the king of all the research. -This is an accessible example as most of your students took their Flintstones. -The article also demonstrates The Thir...