I recently created a few datasets to facilitate analyzing the interaction between demographics and political party affiliations of US Congressional Districts. My goal was to create this graph: I added this data to Choroplethr and pushed the new version to CRAN. This post walks you through using these datasets, the ...

Did you know that Ohio’s state song is Hang On Sloopy, best known as a hit for the McCoys in 1965? Me either, but this week in the State-Off Tournament we’ll see if seventh seed Ohio (7) can cough hang on against second seeded Texas (2). We’ll also continue building ...

Did you know that Ohio’s state song is Hang On Sloopy, best known as a hit for the McCoys in 1965? Me either, but this week in the State-Off Tournament we’ll see if seventh seed Ohio (7) can cough hang on against second seeded Texas (2). We’ll also continue building ...

Using a ggplot image can make a boring, mundane plot in RStudio truly pop off of the page. While doing so may seem exceedingly difficult, I promise you that it is not. In my case, I am a big Pittsburgh Pirates fan and I wanted to throw together a graph ...

This fall, the R Consortium’s support for advancing data science in medicine continues with the third of three exceptional events, pulling together experts in their fields, including the Covid-19 Data Forum,... The post We’ll be at R/Pharma – Oct 12-15, 2020 appeared first on R Consortium.

theme_web_bw theme_web_classic theme_web_void This will be a very short post compared to the detailed stuff I usually write. Just what it says on the tin – I made some tweaks to my three favorite {ggplot2} themes – theme_bw(), theme_classic(), and theme_void() – to make ...

Spinning on that dizzy edge (Just Like Heaven, The Cure) This post talks about a generative system called Physarum model, which simulates the evolution of a colony of extremely simple organisms that, under certain environmental conditions, result into complex behaviors. Apart from the scientific interest of the topic, this model ...

Co-varying predictors can be a messy business. They make estimates unstable, reducing our statistical power and making interpretation more difficult. In this post I will demonstrate how ignoring the presence of co-variation between predictors when exploring our models can lead to odd results and how we might deal with this ...

Introduction Descriptive statistics Minimum and maximum Histogram Boxplot Percentiles Hampel filter Statistical tests Grubbs’s test Dixon’s test Rosner’s test Additional remarks Reference Introduction An outlier is a value or an observation ...

Lately I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to evaluate complex models. Today’s screencast admittedly does not result in the best performing model you’ll ever see, but it is really fun and uses this week’s #...

Intro 9 Lab_ related category Missing Lab values Outlier Lab values High Lab_Hb levels Low Lab_Neu High Lab_Sugar 10 CS_ cultures related category 11 Abx_ antibiotics related category 11i Class of empirical antibiotics given 11ii Antibiotics given Number of antibiotics given 11iii Duration of antibiotics 12 Care_ continuum of care status ...

Introduction Descriptive statistics Minimum and maximum Histogram Boxplot Percentiles Hampel filter Statistical tests Grubbs’s test Dixon’s test Rosner’s test Additional remarks Introduction An outlier is a value or an observation that is distant from other observations, that is to say, a data point that differs significantly from ...

Co-varying predictors can be a messy business. They make estimates unstable, reducing our statistical power and making interpretation more difficult. In this post I will demonstrate how ignoring the presence of co-variation between predictors when exploring our models can lead to odd results and how we might deal with this ...