Mortality Nuggets: Videos on 2020 Death Rates by Cause of Death, Querying WONDER, and Actuarial News
...plus Actuarial Fairy Tales! This little piggy went to the stock market....
Video Version of my Post on 2020 Death Rates
For those who prefer videos:
I collect these sorts of videos in my Mortality with Meep playlist, which is one of the many playlists on Meep’s Math Matters YouTube channel. I created the channel back in 2009, if I remember correctly, and you can see some of my old videos from back when YouTube used to enforce a 10-minute limit on uploaded videos.
You can see they no longer enforce such a limit.
The related post, for your convenience:
An Intro to Causes of Death on CDC WONDER
If you’d like to investigate causes of death on the CDC databases on WONDER, here is a video giving you a quick introduction:
I have a different playlist, called Working with WONDER, where I’m gathering all my CDC WONDER demo videos. The next video I plan on doing is showing how I queried WONDER to create ranking tables.
Celebrating One Year of Actuarial News
Actuarial News is a website Stu created for me to use as a place to collect all the articles, websites, data sources, etc. that I like to use for my research and writing. I tend to develop ideas over long periods, and I prefer my selections over trying to use regular search.
As noted in the video, I used to use the old Actuarial Outpost (RIP) as a repository for my articles on public pensions and finance, but now I use Actuarial.News.
By the way, for any readers seeking actuarial discussion as once was provided by the old Outpost, check out goActuary. I have a thread on spreadsheet screwups and one on non-pandemic mortality, for instance.
Actuarial Fairy Tales
Finally, a little levity:
Actuarial Fairy Tales is a book written by John Lee, an actuarial tutor in the UK.
You get to hear the horror of Sleeping Actuary, who finds herself locked in sleep due to a circular reference in a cursed Excel spreadsheet! The cautionary tale of the 3 little actuarial pigs, where one must not be lazy in setting assumptions in building models. And much, much more.