General question- does combining the 2013 and 2014 survey make sense, given that we expect a lot of overlap (same people surveyed)?
Also, why treat EA as a latent variable when it was directly surveyed? Shouldn’t we just combine by saying if you answered Yes to an EA questions, you are EA?
Well, one thing was definitely changed was my approach to the coursework. I started taking a lot of notes as a memory aid, but then when I worked through problems I relied on what I remembered and refused to look things up in the text book or my notes. This forced me to figure out ways to solve problems in ways that made sense to me- it was really slow going at first but I slowly built up my own bag of tricks.
Glancing at the data, it looks like the median EA at several ages gives 0 as well as the median non-EA. You might want to separate the 0 set from everything else and then answer two questions:
what percentage of EAs/non-EAs donate any money when they give, how much do EAs give, how much do non-EAs give.
I think this makes more sense then what is happening now- the lines don’t seem to fit the data very well.
Can you give an example of the level where things suddenly become more difficult?
As I said in another post, I struggled quite a bit with early calculus classes, but breezed through later “more difficult” classes that built on them.
Also, I disagree with the math and stats thing. Many of the best statisticians I know have strong grounding in mathematics, as do many of the best data scientists I know.
Of course he would have gotten an A. The difference between being good and bad at math is whether you need to “spent all waking hours talking about calculus” to get an A.
Extrapolating from 1 course is silly. I worked like a demon to do mediocre (low Bs) in both calc 1 and physics 1, but somewhere towards the end of my freshman year of college something fell into place for me. By my first year of grad school I was breezing through quantum field theory and math methods for string theory courses with minimal effort.
I worked it out back of the envelope, and the probability of being kidnapped when you blink is only 1/5^^^5.
Both numbers seem basically arbitrarily small (probability 0).
Since the planet has so many distinct people, and they blink more than once a day, you are essentially asserting that on that planet, multiple people are kidnapped and tortured for more than 50 years several times a day.
However, 3^^^3 just so unimaginably enormous that blinking for even the tiniest fraction of a second increases the probability that you will be captured by a madman during that blink and tortured for 50 years by more than 1/3^^^3.
This seems pretty unlikely to be true.
I think the bigger issue with metamed is that they are trying to fill a role that already exists in the market. UpToDate is a bigger, more ambitious company (instead of generating per-patient reports they have a huge database of research summaries curated by actual experts for each disease) that almost all academic medical centers already pay for.
Evolution is a super slow optimization process, and the environment changes. I’m equally “genetically fit” (i.e. I was born to survivors) to any thing alive today, but have a very different goal set.
Actually, now that I think about it, it is potentially not true that you would pay more in premiums than the payout, since insurance companies can make a profit on people who let their insurance lapse before dying
Wait? You are using whole life? Buy a 30 year term policy (get ~5-10x the coverage benefit) and invest the difference in the premiums. You’ll be way better off. Or get some guaranteed no-lapse universal life. Whole life in is never the answer.
Easier to solve the idealized general case first, so that you know what a solution even looks like
This is not generally true, in my experience. Real world problems come with constraints that often make things substantially easier. The general traveling salesman problem for high N might not generally be tractable, but a specific traveling salesman problem might have all sorts of symmetry you can exploit to make things doable.
I’m reminded of a friend in grad school who created an idealized version of some field theory problems, axiomatized it, and was demonstrating the resulting system had all sorts of really useful properties. Then his adviser showed him that the only field theory that satisfied his axioms was the trivial field theory…
The assumption here is that the options are being priced with Black-Scholes, which I don’t think is true.
So back when I worked for a major bank, no one was really using Black-Scholes for pricing anymore. For specific uses cases, there very much are (proprietary) better options, and people use them instead of just making ad-hoc adjustments to a broken model.
Well, as I said, there is either excess supply or unsatisfied demand—that’s pretty empirical.
But you shifted it to “excess supply or unsatsified demand at the prevailing price” which is a much harder thing empirically. Demand is itself somewhat hard to measure, but supply is easy, just measure inventories.
You claim that “market clearing” doesn’t imply there are no excess inventories, I claim that it does.
We don’t end up with surplus inventories (mostly) because the situation is dynamic: both the prices and the people adjust over time
This is the definition of market clearing. The market clearing price is found, and everything sells.
So now it sounds like you agree that in a market that has “cleared,” everything sold.
So empirically, what is the difference between a market that hasn’t cleared vs. one that has, in your view? What would that look like in terms of inventories?
The usual definition of market clearing implies that we don’t end up with surplus inventories building up over time (because everything is sold), etc.
I think “markets clear” implies the market finds the market-clearing price, in which case everything gets sold (i.e. no surplus inventories over the long run).
If your goal is to show that Omega is “impossible” or “inconsistent”, then having Omega adopt the strategy “leave both boxes empty for people who try to predict me / do any other funny stuff” is a perfectly legitimate counterargument. It shows that Omega is in fact consistent if he adopts such strategy. You have no right to just ignore that counterargument.
This contradicts the accuracy stated at the beginning. Omega can’t leave both boxes empty for people who try to adopt a mixed strategy AND also maintain his 99.whatever accuracy on one-boxers.
And even if Omega has way more computational than I do, I can still generate a random number. I can flip a coin thats 60⁄40 one-box, two-box. The most accurate Omega can be, then, is to assume I one box.
In many (probably most?) games we consider the opponents strategy, not simply their next move. Making moves in an attempt to confuse your opponent’s estimation of your own strategy is a common tactic in many games.
Your “modified Newcomb” doesn’t allow the chooser to have a strategy- they aren’t allowed to say “if I predict Omega did X, I’ll do Y.” Its a weird sort of game where my opponent takes my strategy into account, but something keeps me from considering my opponents.
It’s a quite bit more general than Lagrangian mechanics. You can extend it to any functional that takes functions between two manifolds to complex numbers.