Benjamin Scheich is the Director of Data Analytics at the Association of Women’s Health, Obstetric and Neonatal Nurses (AWHONN). His interests include maternal mortality quality improvement, acuity tool development, and data mining methods to better manage customers. He has published numerous articles in peer reviewed journals and spoken at national conferences. He is passionate about learning new data analysis methods and techniques. Ben often attends meetup events organized by the data science community in Washington, D.C. He is a member of the American Statistical Association.
The Association of Women's Health, Obstetric and Neonatal Nurses (AWHONN) created the Perinatal Staffing Data Collaborative in response to the release of its Guidelines for Professional Registered Nurse Staffing for Perinatal Units. In this article we summarize the findings of the AWHONN Perinatal Staffing Data Collaborative from 2011 through 2012.
I was recently tasked with creating a dashboard for our Board of Directors. Our Board needed an easy way to view the financial and operational health of the organization. Building a dashboard that could be updated real-time was new to our organization, and I was excited to lead the effort.
While we have two Tableau Desktop licenses, building a dashboard with Tableau was not an option. I’ve found that requiring users to download Tableau Reader to view the dashboard is often difficult for the user, and sharing a package workbook to update the data is cumbersome.
We have a Tableau license here at work, but I’m always trying to replicate Tableau’s output into R. Recently, I was thinking about how to place summary “Totals”" in a bottom row of an R table, and I realized that it was something that was not discussed much in lectures I attend. Most likely, it is considered too easy to discuss, but it is incredibly important when presenting certain types of data.
A colleague stopped by my office the other day and asked me a simple question: Why do we often see the mean of sample of data published in journal articles? I’m sure you are thinking, “why aren’t you talking about something more interesting with your work colleague, like your NCAA tournament bracket?” Well, the short answer is my bracket had already busted, so I’d gladly talk about anything else. Now, back to addressing the question at hand: my colleague’s reasoning was that the readers are most comfortable with seeing the mean, as they are most familiar with it from their statistics classes in high school.