Election Day Exclusive: Up Close With Dr. M. Genevera! - Umberto Tosi
|Yogi Berra's 1998 book.|
"When you come to a fork in the road, take it," my favourite among the many koan-like paradoxical malapropisms for which the legendary New York Yankee catcher Yogi Berra is famous. Here we are today, November 3, 2020 at such a paradoxical fork, which we have no choice but to take. It just happens to be my turn in the rotation of esteemed, Authors Electric members to post my blog on the third of each month, this time, falling on U.S. Presidential election day. We won't know its fateful results as of this posting, not until very late in this day, perhaps not for days, weeks, even months to follow. But a mighty fork it is!
This is one of those days in which the cliche that "nothing will be the same after this" is for real. Today marks one of those divides whose gravity you just can't exaggerate: The end of the American republic? Possibly. Like the day Julius Caesar declared himself dictator of the 500-year-old Roman Republic? The the American or the French Revolutions, Black Thursday 1929, or January 30, 1933 when Hitler was named chancellor of Germany, or D-Day, or Hiroshima Day, August 6, 1945, the 1963 assassination of JFK, or, of course, 9/11 whose toll has been dwarfed by the daily dead our Trump-botched COVID-19 pandemic.
Yogi Berra also coined, "it's deja vu all over again." Is it 2015 all over again? Full disclosure: I am encouraged by the final day's polls in Joe Biden's favour but filled with foreboding nonetheless. I take no solace in my too damn prophetic pre-election, AE blog of four years ago ("All Politics Is Personal," October 3, 2016) which seems all too relevant to this moment as well. I hope I am wrong this time.
At this point, folks, we must turn to a higher authority. In the spirit of Yogi Berra, I offer this interview with a pioneer in the science of statistics who will help us sort out Election Day conundrums.
UP CLOSE WITH THE DOYEN OF DATA SCIENCE
|Dr. M. Genevera and her famous formula.|
No one's name has been cited more often in connection with probabilities than that of the under-sung queen of data science herself, Dr. Marge Genevera, Nobel Laureate and Princeton professor of mathematics. Despite pollsters citing her with their every projection - whether in science, economics, or politics - few have been less understood, and less credited for her breakthrough discoveries in statistical analysis than the reclusive Dr. Genevera.
Today, on this Tuesday, November 3rd, in the final hours of U.S. Presidential voting, her theories will be tested to the utmost - with historic consequences for her field and for the world. Therefore it is with great pride that I present this rare and exclusive interview.
UT - First of all, thank you, Dr. Genevera for taking your valuable time to be here on what must be a busy day for you.
Dr. Genevera - Busy indeed, Mr. Tosi, and thank you. It's my pleasure. I don't get often get a chance to reach out to a wider audience such as yours.
UT - Do you feel like the news media ignores you? I mean, you the scientist and your work?
Dr. Genevera - It's more about mentioning me, but ignoring what my theory means in the context of their citing it - if that's clear.
UT - I'm not sure. But it goes beyond mere mentioning. Four years ago, many media pundits blamed you - or your theories - for misleading them and the public about Donald Trump's upset victory in the presidential race against Hillary Clinton.
Dr. Genevera - That's because they don't understand the meaning of my work.
UT - In what say, Ms. Genevera?
Dr. Genevera - They think of my name, not as a caveat, but as some sort of option.
UT - Meaning? Option for what?
Dr. Genevera - A sort of indicator that says: 'Insert wish here.'
UT - So, what should people think when they hear the phrase '...within a Marge Genevera'?
Dr. Genevera - They should know what it means - shorthand for my equation...
UT - That is?
Dr. Genevera - That one can trust the accuracy of a projection as being within fixed limits - calculated by multiplying a critical factor (for a certain confidence level) with the population standard deviation, and then the result is divided by the square root of the number of observations in the sample.'
mathematically expressed as:
MOE = Z * ơ / √n
UT - So, MOE? Within a Moe?
Dr. Genevera - You could put it that way...
UT - and leave your name out of it?
Dr. Genevera - Yes, but stick to the percentage limits. Don't draw conclusions beyond those limits.
UT - So, think of it as a caveat. If a newscaster says Joe Biden leads Donald Trump by five points in Pennsylvania with, as they say, 'a Marge Genevara' of 5 - or as you put it of 5 Moes - then it's the same as the two being even - a 'statistical tie.' Right?
Dr. Genevera - If engineers were as careless with my formula in calculating stress tolerances, as news people are with it when applied to polls - well then, dams and bridges would fail all over the place- within a certain MOE, that is.
UT - A good rule to keep in mind, although given the sorry state of our infrastructure, that could be the case anyway. One last question before we go to break: What you have said casts doubt on a wide swath of polls that have been reported during the electoral campaigns. Truth be told, very few poll results range outside an MOE of 5 percent - a pretty wide range of fudging. Therefore - by your reckoning - they've been a wash - kind of self-nullifying. Considering that, can you leave us with any reasonably dependable final predictions on the outcome of today's elections?
Dr. Genevera - Biden-Harris within an MOE that allows everything to go either way.
UT - That's what I thought you'd say. Well, thank you, Ms. Genevera. It's been an honor to have you on our program. Give my best to Moe as well.
Dr. Genevera - Thank you! And, with all humility, remember, Genevera's Law: 'Nothing is certain even when you take Marge Genevera's Law into account.'
Back to Yogi Berra, who also said, "It ain't over 'til it's over."