Raul took what I wrote and ran with it in one direction but my only point was that the 2nd version (34^~-.0.01) is nice because it directly incorporates the two numbers mentioned rather than using (what we all know is) 0.99=1-0.01 (or -.0.1).
There's a possible example of Bayesian updating here if, instead of a point value like 0.007, we use a distribution centered on 0.007 and update this estimate based on subsequent information like how many actually die of the disease within a relevant period, say 2 weeks. Introducing a time limit like this also speaks to Raul's addition of a baseline mortality rate of something like 1%/year which also needs to be considered in a more comprehensive model. On Thu, Oct 8, 2020 at 3:21 PM Brian Bambrough <[email protected]> wrote: > The chance that I survive is 0.99. The chance that you survive is > 0.99. The chance for each of the other 32 to survive is 0.99. The > chance that we all survive is 0.99^34 or 0.71. > > On 10/8/20 12:44 AM, Devon McCormick wrote: > > If 34 people have a disease which is fatal about 1% of the time, what is > > the chance that no one in the group dies? > > ) > > 2020 10 7 23 42 40.156 > > 0.99^34 > > 0.710553 > > 34^~-. 0.01 NB. Stating it another way > > 0.710553 > > > > ---------------------------------------------------------------------- > For information about J forums see http://www.jsoftware.com/forums.htm > -- Devon McCormick, CFA Quantitative Consultant ---------------------------------------------------------------------- For information about J forums see http://www.jsoftware.com/forums.htm
