Curated datasets are useful to know about if you want to do a data science portfolio project on your own. I made this blog post for our group mentoring program. Check out the ones I am promoting on my blog!
Tag Archives: data visualization
16
Feb
Feb
Querying the GHDx database is challenging because of its difficult user interface, but mastering it will allow you to access country-level health data for comparisons! See my demonstration!
20
Jan
Jan
Interview preparation for data science jobs can involve taking several simple, actionable steps to make yourself feel confident and ready to answer questions with ease. Read my blog post for my tips and tricks!
Data Science
Dumbbell Plot for Comparison of Rated Items: Which is Rated More Highly – Harvard or the U of MN?
20
Sep
Sep
Want to compare multiple rankings on two competing items – like hotels, restaurants, or colleges? I show you an example of using a dumbbell plot for comparison in R with the ggalt package for this exact use-case!
30
Jul
Jul
Getting data for meta-analysis together can be challenging, so I walk you through the simple steps I take, starting with the scientific literature, and ending with a gorgeous and evidence-based Forrest plot!
21
Jul
Jul
Curious about the American Public Health Association (APHA) – what it does, and where it fits into the bigger picture of public health organizations? I delve into these topics, and explain how you can get involved.
Quality Assurance/Quality Improvement (QA/QI)
Alternative to the PDSA Model for QA/QI in Healthcare? Old-fashioned Epidemiology and Biostatistics! Part 4 of 5
07
Jul
Jul
Want an alternative to the Plan-Do-Study-Act (PDSA) model for quality assurance/quality improvement (QA/QI) in healthcare? I recommend approaching QA/QI a different way, by thinking about the various functions of the QA/QI department.
Quality Assurance/Quality Improvement (QA/QI)
“Bad Blood” Shows how Theranos was an Abject Failure in Data Stewardship: Part 3 of 5
28
Jun
Jun
The book “Bad Blood” describes the fall of startup unicorn Theranos, but also provides insight into the company’s abject failure at data stewardship, which I talk about in this blog post.
Career Development
Two Takeaways from Danny Ma’s Machine Learning Panel: Understanding the Problem, and Understanding your Data
04
Dec
Dec
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.
20
Oct
Oct
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!
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