Showing posts with label measurements. Show all posts
Showing posts with label measurements. Show all posts

Saturday, March 21, 2020

Fun with numbers for March 21, 2020

Recycling some tweets on the third day of California shelter-in-place. Weather is nice:




I really don't like these "flatten the curve" diagrams posing as science



Maybe it’s just me, but this diagram strikes me as a number of unsupported unquantified statements presented as if it’s some sort of quantitative model based on real data
  1. Axes have labels but no scales… so all we can measure is the relative magnitudes. Is that high peak at (D,A) 1%, 10%, 25%, or 90% of the population? Does it happen in a week, a month, or a year?
  2. A/B = 415/110 so this undefined intervention lowers the peak by 73.5%. How many patients is that? Do these measures really slow down infection rates this much? Assuming that there’s no change to recovery speed, that’s a 4-fold reduction from an unidentified intervention.
  3. E/D = 475/280 so this undefined intervention delays the peak by 70%. So if D is a month, this delays the peak a further three weeks, not long enough for a vaccine; if D is a year, that’s another 8 months, presumably enough. 
  4. B is still greater than C, so what happens when the slowed-down process crosses over the health system capacity? Rationing/triage or does this mean bodies littering the streets? That depends on that (B-C)/C = (110-83)/83 or 33% over capacity, but what happens needs absolute numbers, not relative; since there are no numbers, there’s no real meaning.

All the calculations above are just to show that if we’re to take a chart seriously we need to have real numbers and real details, and the above figure is just a qualitative “let’s hope this works to convince people to wash hands and stay away from others” masquerading as a technical models.

BY ALL MEANS, WASH YOUR HANDS, DON’T TOUCH YOUR FACE, AND STAY AWAY FROM OTHERS, because that makes sense. I've been doing it for as far as I can remember.



The information we're getting is preliminary and we're treating it as dogma


From a study of Italian testing:


The internal consistency of this test is 75% (25% of the time the test doesn’t agree with itself in retesting); this doesn’t mean that the test is 75% accurate, because that’s measured relative to the underlying condition. This is an upper bound on the accuracy of the test, since we know that at least 25% of the time it's inaccurate for sure. (Sample size appears small, but for Medicine this is almost their version of "big data.")


A more general point about COVID19 testing


It's easy to show that missing covariates leads to panic-inducing overestimates. The following numbers are not COVID19 data, just an illustration


Sometimes I despair of what people try to do with small amounts of data, and then the sarcasm comes out:
How can anyone deny this calamity?! In less than two months the entire population of the Earth will test positive. 
In 100 days, over 8 trillion people will test positive. That's 5 times the total number of humans who've ever lived!!!! 



TSLA twitter, always good for a laugh



No matter what the stock does or at what price it's trading, Ross always says "buy." One wonders how he charges 2-and-20 to his clients to give advice of this quality.



Richard "Hamster" Hammond drives a Tesla Model X



And gets very excited at adding one mile every few seconds at a Tesla Supercharger. (We can see in the touchscreen that the Supercharger is delivering 65 kW and Tesla claims 310 Wh/mi,* so that would average out at about 16 seconds per mile of range.) Not to be a spoilsport, but a gas pump adds about 26 miles of range per second (3 l/s in a 35 MPG car).

Then there's a small blur fail that reveals Hammond isn't really driving under the speed limit:


That's okay, Mr. Hammond, no one else is either.

- - - - -
* If you believe that number, you're exactly the kind of investor I'm targeting with a new product structured mostly with 2020 pandemic cat bonds; act now, supplies are limited.**

** CYA statement: this is a facetious offer, expressing derision for Tesla's number, not a proffer of a tradable security structured from out-of-the-money cat bonds.



Some videos to watch while the economy tanks around us



Grant Sanderson of 3blue1brown gave a talk at Berkeley about having people engage with math. The gist is that people want relevance and/or a story. That's good advice, but I think 3B1B's problem is that his audience is self-selected. In other words, that's how you engage an audience that's predisposed to look for and watch math videos. Still, good points.



Experimentboy is back, with thermal cameras. Very fun stuff.



PhysicsGirl suggests fun experiments to keep us from losing our minds while we wait to be moved to FEMA camps or be turned into Soylent Green.


YouTube affords the überdorks amongst us the opportunity to watch talks waaaaay above our expertise, something that in real life would be embarrassing, not to mention logistically difficult. So here are some links to:

Caltech. MIT-West, as some people who went to a technical school in Massachusetts call it.

Stanford Institute for Theoretical Physics. Fair warning: Susskind eats cookies when he talks, so there's spraying in some videos (all Susskind videos, really).

Institute for Advanced Studies at Princeton.

Nasa Jet Propulsion Laboratory.

Art talks at Le LouvreMusée D'Orsay, the British Museum, the Smithsonian Institution, and the Museum of Fine Arts in Boston, a small town in a hard-to-spell state




Live long and prosper.

Monday, October 22, 2012

Can we stop talking about "manufacturing jobs"?


A lot of people worry about "manufacturing jobs," but the metric is seriously flawed.

Politicians and some financial analysts decry the decline of manufacturing jobs. There has been some decline, but the way these jobs are measured is inherently flawed, as it fails to take into account the change in managerial attitudes towards vertical integration.

Easy to see why with an example:

Ginormous Corp. makes widgets. In the 60s to mid-80s, as it went from being Bob's Homemade Widgets to Ginormous Corp., it added new facilities which had janitorial, accounting, cafeteria, legal, and other support services. All personnel in these support services counted as "manufacturing jobs."

In the mid-80s, Ginormous Corp. figured out (with a little help from Pain & Co and McQuincy & Co consultancies) that these support services were (a) not strategic and (b) internal monopolies. Part (a) meant that they could be outsourced and part (b) strongly suggested they should be outsourced. Let's say that Ginormous Corp. spun out these support services into wholly-owned subsidiaries, with no significant change in overall personnel.

So, all the personnel in janitorial, accounting, cafeteria, legal, and even some of the technical business support went from being in "manufacturing jobs" to being in "service jobs" without any change to what actually is produced and any actual job.

A metric that can change dramatically while the underlying system and processes don't change much is not a good foundation for decision-making. "Manufacturing jobs" is one such metric, as it depends on organizational decisions at least as much as on actual structural changes.

Metrics: useful only when well-understood.

Note: There are many reasons why focusing on manufacturing jobs over service jobs is a bad idea: Old Paul Krugman explains the most relevant, differential productivity increases, here.