Lipedema, a severe metabolic disorder, is more common than originally thought. A non-trivial proportion of women who struggle with obesity actually have undiagnosed lipedema. I am on a research team that just published a peer-reviewed article that presents the ketogenic hypothesis for lipedema, and here, I present a summary.
This lively panel discussed many topics around designing and implementing machine learning pipelines. Two main issues were identified. The first is that you really have to take some time to do exploratory research and define the problem. The second is that you need to also understand the business rules and context behind the data.
On #GivingTuesday, donate to Central Boston Elder Services’ Little Necessities program! Give early on December 1, 2020, and your donation may be matched through a program arranged by the #GIVE65 senior services crowdfunding platform.
Get to know three of my favorite SAS documentation pages: the one with sort order, the one that lists all the SAS formats, and the one that explains all the SAS operators and expressions!
A/B testing seems straightforward, but there are a lot of picky details. What A and B conditions do you actually test? How long do you run the test? How do you calculate the statistics for the test? Answer your questions by taking this LinkedIn Learning course.
SAS is known for big data and data warehousing, but how do you actually design and build a SAS data warehouse or data lake? What datasets do you include? How do you transform them? How do you serve warehouse users? How do you manage your developers? This book has your answers!
Curation files are especially helpful for communicating about data on teams. Learn more about what you’ll learn when you take my online LinkedIn Learning data curation course!
I use the datasets from the Behavioral Risk Factor Surveillance Survey (BRFSS) to demonstrate in a lot of my data science tutorials. The BRFSS are free and available to the public – but they are kind of buried on the web site. This blog post serves as a “map” to help you find them!
I love the Likert package in R, and use it often to visualize data. The problem is that sometimes, I have sparse data, and this can cause problems with the package. This blog post shows you a workaround, and also, a way to format the final plot that I think looks really great!
With all this talk about “flattening the curve” of the coronavirus, I thought I would get into the weeds about what curve we are talking about when we say that. We are talking about what’s called an epidemiologic curve, or epicurve for short. And to demonstrate what an epicurve is and what it means, I […]