Hard to predict how low can trump.2.0 sink, but this newly redesigned “Presidential Walk of Fame” sets a (temporary) record, with plaques (written in his appalling social-media style or lack thereof) by the Agent Orange himself that demean his predecessors and self-agrandizes his own actions, while rewriting history. Hard to find a precedent, except in the most sinister dictatures!
While Nate Silver and his colleagues (as The New York Times Nate Cohn) have brought (part of) the general public to adopt a (more) scientific perspective on political polls, the way to combine them, and the need to keep uncertainty fully quantified (witness this recent “Two Theories for Why the Polls Failed in 2020, and What It Means for 2024” by Nate Cohn for the NYT’s Tilt), the author of this book embarks upon a crusade (and a lengthy rant) against pollsters and analysts and media reporters, with the single, many times repeated, argument that non-responses and undecided voters are crucial for the final election outcome… And that a poll gives a snapshot of the current (time) population opinion, not a prediction of its future state. There is not the slightest trace of statistical depth, there is actually no statistics at all found throughout the book, apart from a section (p.281) entitled “Threats to inferential statistics” (with not no maths either, as a few ratio manipulations and a chapter title invoking Jakob Bernoulli!) do not count as maths!, but a lot of repetitions on the same theme and dismissal of statisticians’ analyses, like Nate Silver’s. Opposing to them the theories of Nick Panagakis, a 1990’s pollster. (Funny enough, the Amazon reviews include one “expert in inferential statistics, the major tool employed by Carl [Alen] in this book” and another one stating that “Carl Allen takes the reader through a journey towards statistical literacy“!) And an R code (p.52) for plotting the outcome of 30 Binomial random draws.
“Unless my efforts achieve far more notoriety than even my most optimistic forecast would predict, [the Proportional Method] is unlikely to go away any time soon.” p.183
“If it seems like I’m picking on FiveThirtyEight a lot, it’s not because there are no other forecasters who are better or worse.” p.235
“Sounding eerily like myself, [Nate Silver] pointed out [in 2008] that `many things can happen’ months before the election.” p.208
Reading through the book (during a trip to & from Warwick) was painful, both for the feeling of being stuck in a plane with a perfect unknown, next seat, trying to force their weird theory upon you and no way to escape their rant, as well as for the terrible style of said book, full of repetitions and one-sentence paragraphs. (Of course, nothing as bad as this time near the 2012 US elections I flew to Des Moines next to an inebriated woman that would not stop blathering about her life!) Or as I imagine a card game addict defending their martingale as a sure way to win against the casino. It is also the first time I see references repeated (in postcripts) as many times as they are cited within a chapter. There is no true insight on how polling companies construct their polling samples, how they post-process outcomes by regression techniques, and no reflection on the unique weirdness of the US electoral system in that a few States determine the outcome (rather than majority votes) and thus how a tiny number of voters (escaping the law of Large Numbers) hold the overall result in their hand.
Thus (as most readers will have forecasted) concluding by not recommending the book!
[Disclaimer about potential self-plagiarism: this post or an edited version of it could possibly appear in my Books Review section in CHANCE. Most unlikely though!]
The riddle of this week was inspired by the latest presidential elections when one State after another flipped the winner from Trump to Biden. Incl. Georgia.
On election night, the results of the 80 percent who voted on Election Day are reported out. Over the next several days, the remaining 20 percent of the votes are then tallied. What is the probability that the candidate who had fewer votes tallied on election night ultimately wins the race?
Assuming many votes, perfect balance between both candidates (p=½), and homogeneity between early and late ballots, the question boils down to the probability of a sum of two normals, X+Y, ending up being of the opposite sign from X, when the variances of X and Y are α and 1-α. Which writes as the expectation
which returns a probability of about 0.14 when α=0.8. When looking at the actual data for Georgia, out of 5 million voters, at some point 235,000 ballots remained to be counted with Trump on the lead. This means an α about 0.05 and implies a probability of 7% (not accounting for the fact that the remaining mail-in-ballots were more favourable to Biden.)
 | David on Bayesian workflow [book review… |
 | Ewan on Tidy up, Claude! |
 | xi'an on Tidy up, Claude! |
| Ewan on Tidy up, Claude! |
| Ewan on Já við viðræðum. Já við Evrópu… |
![2 \mathbb{E}_\alpha[\Phi(-X/\sqrt{1-\alpha})]](https://s0.wp.com/latex.php?latex=2+%5Cmathbb%7BE%7D_%5Calpha%5B%5CPhi%28-X%2F%5Csqrt%7B1-%5Calpha%7D%29%5D&bg=000000&fg=B0B0B0&s=0&c=20201002)
