Tag Archives: Centers for Disease Control and Prevention

AI Careers: Riding the Bubble

If you are a data scientist, you may want to do statistics, but you may also be interested in machine learning and artificial intelligence.

AI careers are not easy to navigate. Read my blog post for foolproof advice for those interested in building a career in AI.

Descriptive Analysis of Black Friday Death Count Database: Creative Classification

The Black Friday Death Count database has a list of news reports of deaths or injuries on Black Friday.

Descriptive analysis of Black Friday Death Count Database provides an example of how creative classification can make a quick and easy data science portfolio project!

Dataset Source Documentation: Necessary for Data Science Projects with Multiple Data Sources

If you work on a big data project with multiple source datasets, you run the risk of forgetting exactly how you blended them together.

Dataset source documentation is good to keep when you are doing an analysis with data from multiple datasets. Read my blog to learn how easy it is to throw together some quick dataset source documentation in PowerPoint so that you don’t forget what you did.

Joins in Base R: Alternative to SQL-like dplyr

In base R, you can execute SQL-like joins, as long as you use the correct code syntax.

Joins in base R must be executed properly or you will lose data. Read my tutorial on how to correctly execute left joins in base R.

Defaults in PowerPoint: Setting Them Up for Data Visualizations

The defaults in PowerPoint are really set up for making presentations, not data visualizations.

Defaults in PowerPoint are set up for slides – not data visualizations. Read my blog post for tips on reconfiguring PowerPoint to make it easy for dataviz!

Portfolio Project Examples for Independent Data Science Projects

Are you a data scientist who is interested in doing independent portfolio projects to sharpen your skills? Then I strongly suggest you get a coach or a mentor.

Portfolio project examples are sometimes needed for newbies in data science who are looking to complete independent projects. This blog post provides some great examples of independent projects you can do with datasets available online!

Rapid Application Development Public Health Style

If you work on front-ends or back-ends of health applications, you are probably already familiar with the concepts of Agile and rapid application development.

“Rapid application development” (RAD) refers to an approach to designing and developing computer applications. In public health and healthcare, we are not taught about application development – but it’s good for us to learn about it, since we have to deal with data from health applications. My blog post talks about the RAD approach I […]

REDCap Mess: How it Got There, and How to Clean it Up

REDCap mess on your hands? The REDCap designers made the application so loosey goosey, you can really program yourself into a messy corner if you don't plan well.

REDCap mess happens often in research shops, and it’s an analysis showstopper! Read my blog post to learn my secret tricks for breaking through the barriers and getting on with data analytics!

Benchmarking Runtime is Different in SAS Compared to Other Programs

How do you measure how long it takes for code to run in different programs? And why would you want to measure something like that? Mainly, the reason to benchmark runtime is so that you can figure out how to optimize your code.

Benchmarking runtime is different in SAS compared to other programs, where you have to request the system time before and after the code you want to time and use variables to do subtraction, as I demonstrate in this blog post.

US Public Health Alphabet Soup Explained: What is the IHS?

The Indian Health Service (IHS) is the federal agency in the United States in charge of reservation health.

“What is the IHS?” is a reasonable question to ask, because there are a few things that are very special about the IHS and its healthcare facilities. At first glance, these special characteristics may seem positive, but they actually have devastating unintended consequences, as I describe in my blog post.

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