On the third day, the count stalls at 97%, and the C1-C2 differential reaches a minimum at 0.1%. A major New York City newspaper walks back it’s prediction of 99% victory for candidate C1 over C2. A popular Bayesian pollster then drops candidate C4 from the overall lead while raising C2 to 50% nationwide electability. Candidate C2 declares victory and begins to move on, yet some important questions remain to be answered. Q. Do the data samples up to 97% reporting obey the central limit theorem? Why or why not? Q. If these percentages (as reported by major news outlets )do not reflect a particular candidate’s chance of election, who should take responsibility for misinforming the public? —Brad
On Feb 5, 2020, at 8:54 PM, Brad Klee <bradklee@gmail.com> wrote:
As the tallying continues well into the next day, the total finally reaches 85%, with candidate C1 and C2 separated by a differential of 2.3%, and the next candidate C3 down 5-10% from C2.
Concerned citizens discover an unfair tally of nearly 500 votes detracting from the total of candidate C2. Thereafter, the committee announces a "minor correction" of 0.9%, and the 86% subtotals have a C1-C2 differential of 1.2%.
As time goes on, the C1-C2 differential continues to decrease, from 1.2% to 0.9% after 92% reporting.
Q. Can major news outlets reasonably declare a winner between candidates C1 and C2?
--Brad
PS Here is the Wiki Page: https://en.wikipedia.org/wiki/Iowa_Assessments
On Tue, Feb 4, 2020 at 4:53 PM Brad Klee <bradklee@gmail.com> wrote:
Did anyone else have to take these tests as a kid? There was no real reward for doing well, but if you fail, you get labeled as "not-up-to-standard". I can't remember any of their problems, but thought of something else today:
An election has five candidates finish with double-digit percentages, though, all less than 30%. After about 20 hours, the committee assigned to count votes decides at first to announce only 62% of all results.
Define an "exclusion scenario" as a set C_1, C_2, ..., C_n of candidates who are announced to have zero percent support on a fair tally of the 62% subset.
How many different exclusion scenarios are possible when allowing for any 62% subset? Is it possible to completely exclude the overall winner?
I think this can be solved using standard combinatorics, but I am wondering if anyone would understand the implications.
--Brad