In my role as an analyst, my team and I are required to put together reports that summarize each hospital’s patient satisfaction performance in a table. These are reviewed by our system’s executive leadership team and the hospital directors in monthly operational reviews (MORs).
A few months ago, Harrison Lavelle wrote a piece for Split Ticket reviewing the electoral challenges faced by house republicans who voted to impeach Donald Trump for his role in the assault on the capitol.
Sometimes, we want a model that generates a range of possible outcomes around each prediction and may opt for a model that can generate a prediction interval, like a linear model.
I’ve never built a house (shocking, I know), but from far too much time spent watching HGTV, I understand the basic gist of it. You lay a foundation, setup framing and walls, route mechanical and electrical, then work on final touches like painting and decorating (to be sure, I’m hand-waiving a lot of detail away here).
Note (3/14/22): This article was written prior to the release of the {workboots} package. Since the release of that package, I’ve discovered some errors with the methodology described here and would recommend instead referencing the post associated with the release.
While the sitting president’s party tends to House lose seats in the midterm elections, the president’s approval rating can help inform us of the magnitude of that loss. In general, the more unpopular the president, the more seats his party tends to lose.
In the year since I started this blog, there’s been a lot that’s happened: I learned to use R, picked up the basics of machine learning, and moved into a new job/industry.
The 2022 midterms are still quite a ways away, however, in order to have a forecast ready in time, I need to start working on the model well in advance!
Happy (belated) Thanksgiving! This year, my family drove down to Houston for the holiday & I hosted Thanksgiving for the first time. We played lots of games and ate well - my fridge is still stocked full of leftovers.
Are y’all ready for some charts?? This week, I did a bit of machine learning practice with the diamonds dataset. This dataset is interesting and good for practice for a few reasons: