Beware the Argument: The Flint Water Crisis and Quantiles

Abstract If your tap water suddenly becomes brown while authorities claim everything is okay, you start to worry. Langkjær-Bain (2017) tells the Flint Water Crisis story from a statistical viewpoint: essentially the interest is in whether the 90th percentile in a sample of lead concentration measurements is above a certain threshold or not. We illustrate how to perform the necessary calculations with R’s quantile function and show that the type-argument of the function matters. This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. The markdown+Rknitr source code of this blog is available under a GNU General Public License (GPL v3) license from . Introduction In a recent Significance article, Langkjær-Bain (2017) tells the story about the Flint water crisis. In 2014 the city of Flint, Michigan, USA, decided to change its water supply to Flint River.…
Original Post: Beware the Argument: The Flint Water Crisis and Quantiles

Better Confidence Intervals for Quantiles

[newcommand{bm}[1]{boldsymbol{mathbf{#1}}}DeclareMathOperator{argmin}{arg,min}DeclareMathOperator{argmax}{arg,max}] Abstract We discuss the computation of confidence intervals for the median or any other quantile in R. In particular we are interested in the interpolated order statistic approach suggested by Hettmansperger and Sheather (1986) and Nyblom (1992). In order to make the methods available to a greater audience we provide an implementation of these methods in the R package…
Original Post: Better Confidence Intervals for Quantiles

Surveillance Out of the Box – The #Zombie Experiment

Abstract We perform a social experiment to investigate, if zombie related twitter posts can used as a reliable indicator for an early warning system. We show how such a system can be set up almost out-of-the-box using R – a free software environment for statistical computing and graphics. Warning: This blog entry contains toxic doses of Danish irony and sarcasm…
Original Post: Surveillance Out of the Box – The #Zombie Experiment