2 perspectives on the relevance of social science to our current predicament: (1) social scientists should back off, or (2) social science has a lot to offer

https://statmodeling.stat.columbia.edu/2020/05/12/2-perspectives-on-the-relevance-of-social-science-to-our-current-predicament-1-social-scientists-should-back-off-or-2-social-science-has-a-lot-to-offer/Perspective 1: Social scientists should back off This is what the political scientist Anthony Fowler wrote the other day: The public appetite for more information

Equipping Your Data Science Team to Work from Home

https://blog.rstudio.com/2020/05/12/equipping-wfh-data-science-teams/ Photo by Djurdjica Boskovic on Unsplash If your data science team experienced an abrupt transition to working at home, it may be a good

“1919 vs. 2020”

https://statmodeling.stat.columbia.edu/2020/05/10/1919-vs-2020/We had this discussion the other day about a questionable claim regarding the effects of social distancing policies during the 1918/1919 flu epidemic, and then

Uncertainty and variation as distinct concepts

https://statmodeling.stat.columbia.edu/2020/05/10/uncertainty-and-variation-as-distinct-concepts/ Jake Hofman, Dan Goldstein, and Jessica Hullman write: Scientists presenting experimental results often choose to display either inferential uncertainty (e.g., uncertainty in the estimate

Standard deviation, standard error, whatever!

https://statmodeling.stat.columbia.edu/2020/05/09/standard-deviation-standard-error-whatever/Ivan Oransky points us to this amusing retraction of a meta-analysis. The problem: “Standard errors were used instead of standard deviations when using data from