“AI on the edge” was a new term for me that I learned from Marc Staimer, founder of Dragon Slayer Consulting, who was interviewed in a podcast. Marc explained how AI on the edge poses a data storage problem, and my blog post proposes a solution!
“What is the MHS?” is a question not always asked by public health data scientists, but it should be. The MHS – or Military Health System – serves the US military through healthcare facilities in locations where civilians do not have access. I provide an explanation on my blog post.
Making upset plots with R package UpSetR is an easy way to visualize patterns of attributes in your data. My blog post demonstrates making patterns of co-morbidities in health survey respondents from the BRFSS, and walks you through setting text and color options in the code.
Making box plots in R affords you many different approaches and features. My blog post will show you easy ways to use both base R and ggplot2 to make box plots as you are proceeding with your data science projects.
Convert CSV to RDS is what you want to do if you are working with big data files in R GUI and want to improve efficiency. Read my blog post for an explanation and video demonstrations of this process!
GPower case example shows a use-case where we needed to select an outcome measure for our study, then do a power calculation for sample size required under different outcome effect size scenarios. My blog post shows what I did, and how I documented/curated the results.
SAS University Edition is free to use and helpful for the learner, but it is honestly very hard to download and set up, because there are many complex steps. SAS provides guidance, but there are a lot of confusing parts to the process. This post is the second in a four-part series that helps walk […]