davidxc

This is really amazing, thanks for building and sharing this!

I don't think "most appeals" is accurate. It's the aesthetic that results in the most profit, which just means that it's optimal in terms of making tradeoffs between level of appeal to various consumer segments, price points, cost to manufacture, etc.

But maximizing profit and the tradeoffs that result from that are definitely not equivalent to most appealing to the general population.

Best of luck! Your attitude is really inspiring.

I never said that P/E ratios in the US are "too high". I said that they've been higher in recent years than in past history.

This is, as you said, because the amount of money chasing investment opportunities is increasing. I agree that the reasons for this are complex, but one significant reason that the amount of money chasing investment opportunities is increasing is central bank stimulus (not just in the US, but worldwide).

The rise of asset prices definitely is a much more complex issue than just US policy, but I'd still argue that stimulus by the US is one of the causes, not only a symptom.

I agree with you that the US has been more successful in managing the 2008 crisis than the ECB, and that part of that was because we recognized that we needed stimulus earlier on in the crisis. But this doesn't contradict anything else that I said.

I also never made the claim that the counterfactual of no stimulus would have been better - I personally believe it would have been worse, since the economy and labor market would have likely went through a longer and more serious collapse. But again, this does not contradict what I said about central bank stimulus being one of the significant causes in the rise of prices in financial assets.

The statement about the lack of inflation from QE and other stimulus programs from 2008 is pretty questionable. There's been little inflation as measured using usual consumer price indices, but the construction of those indices is typically fairly focused on consumer goods and underweights the assets that rich people tend to invest in (stocks, real estate, bonds, etc).

The QE and stimulus programs from 2008 were significantly more targeted toward the upper and upper-middle classes (arguably without that much trickle-down), and so there wouldn't be much significant inflation as measured by consumer price indices.

But if we look at the assets that rich people invest in (since it's mostly wealthier people who benefited from the 2008 stimulus programs), then I'd say there's been a significant amount of inflation - P/E ratios for stocks have been historically high in the last few years, real estate in desirable cities has gotten significantly more expensive, and bond yields have been low.

We seem to be already seeing some of the same, with the stock market being pushed up by the Fed's commitment to 4T+ in stimulus this time around and ever lower interest rates.

I believe my real analysis class made me a significantly better programmer and thinker in general, but I don't use anything specific from it (not yet, anyway).

Look up tax incidence and elasticity of supply / demand curves. Yes, it could definitely be reasonable to assume, from a modeling perspective, that companies currently charge the optimal price for maximizing profit. However, once you impose extra transaction costs on companies (like a tax), the equilibrium price will then change (previous equilibrium is no longer the equilibrium because external state has changed).

By your argument, taxing a transaction in a market would not ever raise the price charged to the demand side. It's pretty easy to see by reading a chapter about tax incidence (which is different from where the tax is legally placed) and elasticities of supply/demand curves that this is definitely false (not just in theory, but also in practice)

As someone else said below, treating STEM as one category is absurb and lumps together way too many different majors and careers (that have drastically varying levels of attractiveness and compensation growth).

Majors like biology and chemistry have fairly terrible prospects with just a BS degree, but CS and the engineering majors are still quite good. Physics and math are more iffy, but if you know what you're doing and pick up some employable skills on the side, then those majors will at least get you into interviews for good jobs.

There's also the question of what "not enough jobs" means. There are definitely struggling CS majors, but I think that a statement about there not being enough jobs needs to be looked at in a relative way - that is, one needs to consider what the alternative options are and whether those alternatives have better prospects. Many careers have been on the decline, and it's difficult to really identify career paths that are significantly better than computer science / software engineering (at least, at the undergraduate level). Even if we compared careers that required graduate school, the only paths that one could plausibly argue are significantly better than tech are medicine, law, and business (in my opinion). Those three careers all come with their own serious tradeoffs and downsides.

If anyone has information on what career paths are significantly better than CS / engineering, I'd be interested to hear your opinion. Right now, I'm unfortunately not seeing significantly better alternatives.

Consider the defense industry / government contractors. I'm not sure what kind of salary you're looking for, but the defense industry / gov contractors pay fairly well (I'd guess ~150k ish for someone with your background) and checks most of your requirements.

Here's a more simple thought experiment that gets across the point of why p(null | significant effect) /= p(significant effect | null), and why p-values are flawed as stated in the post.

Imagine a society where scientists are really, really bad at hypothesis generation. In fact, they're so bad that they only test null hypothesis that are true. So in this hypothetical society, the null hypothesis in any scientific experiment ever done is true. But statistically using a p value of 0.05, we'll still reject the null in 5% of experiments. And those experiments will then end up being published in scientific literature. But then this society's scientific literature now only contains false results - literally all published scientific results are false.

Of course, in real life, we hope that our scientists have better intuition for what is in fact true - that is, we hope that the "prior" probability in Bayes' theorem, p(null), is not 1.

Make sure you apply to more schools than the three you listed (MIT, Penn State, Stanford). Based on the information you provided in your post, you're definitely not guaranteed to be accepted to MIT or Stanford (there's a very significant chance that you'll be rejected). MIT and Stanford both reject many applicants with profiles similar to yours (or better than yours) each year.

I'm partly speaking from personal experience. I had similar stats to you (4.8 GPA weighted, 3.9+ GPA unweighted) in high school and a 2330 SAT (780 math / 780 reading / 770 writing). I also had very high standardized test scores in other areas and numerous extracurriculars / state and national level awards.

I ended up getting rejected from both Stanford and Princeton (though I did get into Yale). Basically, the top colleges are a crapshoot even with stellar stats, and you should really apply to 7-10 colleges with some backups mixed in.

As far as where to go, I'd just give the general advice of making sure you don't take on a significant amount of debt. If you're middle class, MIT, Stanford, and the Ivies should give a lot of financial assistance. It's debatable whether prestigious colleges actually provide better education than good state colleges, but the prestige associated with a top school will help you a lot in the future (like it or not, most of the world is not anywhere close to an approximate meritocracy, which means that prestige will play a significant role in the opportunities open to you after college).

In my opinion, there are plenty of useful things to do as a programmer. There are many non-profit organizations doing important work that would love to have a volunteer programmer. You could also teach math or programming to high school kids, etc. Paid programming work can sometimes seem far removed from "useful" work, but I think that's partly because of the complexity of society and all the abstractions that we have built. If you'd like to do something that feels more direct, I would suggest volunteering somewhere. But I do agree with your sentiment that finding meaning on your own can be quite difficult.

That website looks good. Thanks!

Common Lisp has macros. Paul Graham's book On Lisp is usually pointed to as the best treatment of macros in Lisp. CL also has many more features than Scheme, as mentioned in the other comments here.