pyduan

The best part is that now that it's been posted it has now become impossible to disagree, because attempting to disprove it would actually validate the law.

Aside from the other problems that have been pointed out, this would provide an incentive for prisons to favor groups that have been statistically linked to lower recidism rates -- not only could it create some kind of favoritism, it would also probably favor those who perpetrated more serious crimes (thieves have by far the highest recidivism rates, much higher than, say, murderers [1]).

The American penitentiary system is fundamentally flawed and is in need of a deep reform; the real shocker to me is that stuff like this can happen before trial:

> Nazario first went to Rikers at 16, after an arrest on an assault charge. Before leaving at 19, he says, he had spent more than 300 days in solitary confinement — all before being convicted of a crime.

(on a side note, I was surprised to learn Rikers is actually a jail and not a prison)

[1] http://www.bjs.gov/index.cfm?ty=pbdetail&iid=1134

Well I would say that as far as Chu is concerned, any long term consequences his actions may have on the game are likely to be mere externalities to him since these will probably not happen until he's already extracted the value he wanted out of the game.

You could also argue that the additional publicity he's enjoying thanks to his unusual strategy (eg. this article) far outweigh the costs of any such potential negative externality.

I think you may have misinterpreted my comment (you know I don't work for Square right?).

> Hard problems should be challenges, not excuses.

Which is precisely why I mentioned in my original post that my preference (and Eventbrite's) goes towards doing the opposite and trying hard to give the user the benefit of the doubt. By doing this we expose ourselves to more risk because we want to transact with everyone -- without risking to disclose too much about our policies, you'll notice our system is very tolerant for mistakes and missing inputs, and in case something does go wrong we have a dedicated support team to deal with these issues. This makes building and training our algorithms that much more complicated if we want to keep our risk profile in check but it is a trade-off I'm happy to make, so I'd like to think I'm not guilty of what you're accusing me of.

Overall, my point was just to provide some context on where Square comes from since OP seemed confused about what they perceived as a ridiculous policy. The comparisons you picked (Comcast, Google) are a good example of why it's interesting to talk about fraud (which is a topic we rarely have in mind when building or using payment services): fraud is not a simple inconvenience for startups -- it's something that can potentially put the entire business at risk, so you have to have both the ability and the willingness to take on that risk. In the absence of controls I can think of many ways to defraud Square out of millions of dollars in the matter of hours. They're strong enough to take the hit it now, but one single such attack while they were younger could have put their success in considerable danger had they not taken some precautions.

Of course this is no excuse for not having a friendlier or more reactive support, but Square or not Square I just felt this is a topic worth bringing to the spotlight.

(Disclaimer: I write fraud detection algorithms for Eventbrite, and work closely with the team that built the fraud systems at PayPal.)

I'm sorry this happened to you. I personally believe the burden of proof should be on the company. However, that some choose to err on the side of caution is perfectly understandable.

The thing is that companies that handle credit card payments are very vulnerable to fraud because they are liable for consumer chargebacks [1], at least in the US. This is particularly unfortunate since US cards also happen to have pretty poor security (which also has probably something to do with the fact the merchants are liable, and not the banks). Stolen credit card numbers are extremely easy to obtain (cf. Target breach) [2], and once this is done fraudsters have basically two main ways to extract money out of it:

1) Use the card number to make purchases online, or better yet, find a self-service platform that lets you become a merchant then purchase your own offerings (eBay/PayPal, Eventbrite, etc.).

2) Duplicate the card (made much easier by the US' slowness in adopting chip-and-pin), and use it to pay for goods or to load the money on some account. Square is perfect for this since you own the card-reading device, which makes it much less risky than attempting to use a duplicated card at an ATM or at a retailer.

Now, the problem is that you potentially need a lot of cushioning to withstand fraud attacks: while the processor only makes profit from the transaction fee, they are liable for the entirety of the charge, so one single fraudulent transaction can wipe out the profit of thousands of good ones. Being attacked by a fraud ring for hundreds of thousands or even millions of dollars in a single day is not impossible (in fact we've seen this happen, and Eventbrite's transaction volume is much smaller than PayPal's or even Square's), so this is a lot of risk to take on for a company, especially a startup.

Regarding the bad customer service you've received, there is a specific reason why companies often decline to comment on fraud security checks: by allowing you a way of recourse, they would be disclosing information about how their system works, which makes it potentially vulnerable to attackers. For example, if they said "sure, just send us a copy of your driver's license and we'll lift the ban", this would be a signal for fraudsters to try to fake such documentation.

Overall, it's a complex issue and unfortunately frustration is part of the game (trust me, if PayPal could have found a way to make operations smoother and less frustrating, they'd have done it). At Eventbrite we've chosen to assume this risk and be more liberal with verification because we decided that providing a good user experience is worth losing some money over (and because we have faith in our ability to keep up with the fraudsters), but this is a decision every company that handles money has to make and it's not an easy one.

[1] http://en.wikipedia.org/wiki/Credit_card_fraud#Merchants

[2] fun fact: you'd be surprised to see how big this underground economy is; it's so well-oiled that some sellers even provide customer service on the credit card numbers they sold, and offer money back guarantees if the card has already been deactivated

The "average" is not a technical term in statistics. It's a shortcut in everyday speak for some measure of centrality. What you're referring to is (probably) the arithmetic mean, but the average can be any other measure (for example, when you talk about "average speed" you're not using the arithmetic mean, but the geometric one), including the median.

Also, in this case the mean and the median are probably close to the same thing since recruiter skill is likely to be normally distributed, but that's a different story. </nitpick>

Given Google's emphasis on quantifying every aspect of recruitment, I wouldn't be surprised if the reason is because their numbers show that contacting people who previously rejected offers was more likely to result in a hire than contacting people who never interviewed, and that they decided that ignoring "do not contact" instructions was worth it after some time. Basically, kind of an retargeting strategy but applied to hiring. I understand why this may be annoying to you, but your case is probably rare enough that they decided to go along with it -- I would think that most people do not care enough about being contacted by companies they do not want to work for to complain. I do not condone this but the assumption that you may not feel as adamant about not working at Google as you did two years ago (during which a lot can happen) seems perfectly understable to me.

With that said, your post does come across as really obnoxious. Asking to have an "ON PAIN OF DEATH" mention added on their file? Really? I dislike having my instructions disobeyed as much as the next guy, but if I counted properly this is 6 emails over more than 7 years. Surely one could live with receiving one unwanted email every year or so? It's not like it's that hard or time consuming to just ignore a message or to decline politely -- after all, a lot of people do it multiple times on a daily basis, and I'm sure you do too.

This is too bad, because the tone of your post distracts from the perfectly valid (but IMHO, minor) point that this policy does imply things about Google they view themselves.

This feels like pure numerology to me, with the entire argument being based on some vague numeric coincidence. I have no experience in food manufacturing, but I'm willing to bet there are much easier ways to mix dough at any desired proportion than the one described here.

Here's another, potentially simpler explanation: I am no pastry chef, but it seems these recipes often use a 2:1 mix of different types of chocolate (e.g. dark and milk) [1]. Now if the recipe contains 1/4 of one type and half of this of another type, that's 25% + 12.5% = 37.5%, which is about as close to 37% than 1/e. Ta-da!

And this is just one explanation I just made up on the spot; I'm sure one can find many others by playing around with the numbers. I don't know for sure what the real answer is or if there even is one (it could just be that marketing thought 37% sounded more elaborate than a round number like 40% while also costing less to produce and tasting the same), but one shouldn't forget to apply Occam's razor here.

[1] a quick Google search gives me this: http://www.talkfood.com/forum/showthread.php/3230-37-Chocola...

Interested in getting in touch, although I may not be able to give you exactly what you're looking for. I grew up in Paris and am currently looking to start a company in SV, so I'm curious about what prompts you to do the opposite journey.

This is great. For a weekend project this looks and feels very polished.

Possible suggestions: it looks like it is 'just' retrieving one's list of subscribed subreddits then displaying manually curated lists for each category, which means every user who is subscribed to a subreddit will be shown the same products in this category.

I don't know if you are planning on continuing work on this project, but if you are adding more items implementing an actual recommender system could do wonders (for example, by looking at what users with similar subscriptions have favorited). I feel the Reddit-browsing demographic is one that would be very receptive to this type of thing since some subreddits are all about about social-based discovery.

I'm willing to guess one can learn a surprising lot about one's preferences by looking at their Reddit subscriptions. For example, you may be able to guess the clothing style of someone who is subscribed to r/malefashionadvice, r/newyork, and r/finance, or that someone who reads both r/audiophile and r/metal might like different headphones than someone who participates a lot in r/classicalmusic.

I think there is a fundamental difference you're missing between the experiences you're describing and that of online dating: it's not so much about the amount of noise and more about the signal-to-noise ratio, as well as the overwhelmingsness of the situation that the author argues makes dating websites (not life in general!) a difficult experience.

On a dating website, messages are the only signal available to the receiver. This means the person had to go through a lot of noise (or as the article says, "wade through a mountain of shit") to find out if anyone interesting to them messaged them. If on top of that these messages are as numerous and off-putting as the person in the article says, then it's easy to see the online dating experience can become rapidly unpleasant. Furthermore, this is a problem because finding matches is the only function of a dating website!

Now, back to your example. The thing is that not only do you hopefully get utility from socializing at a bar beyond being able to find sexual partners and you're presumably not constantly in such a situation (which already makes your analogy miss the point), but you have many other signals at your disposal: you can simply visually identify those who are more attractive to you in the room and physically make your way through them, and even though, as you said, you can get cockblocked at times, this is still an option that's not available to people on dating websites.

> This is bollocks, for the most part. There have been plenty of studies... my state was doing a lot of research... studies here and there would filter through... this is not reliant on a single study with a small n.

There is a missing piece of information in your comment. Does this mean the studies you've seen were contradictory? You mention there have been a lot of studies done about the subject but not the results. Can you elaborate on why you reached this conclusion?

I'm genuinely curious about what makes you think so -- the research I've been able to find all seem to corroborate the benefits of napping [1], and I've always been under the impression power naps were effective myself.

I wrote another comment here about how a small n can still produce surprisingly statistically significant results, but besides that it also looks like there are many more than one study on the topic.

> I would have thought that a startup founder who bases his company on the premise of napping would have read more on the topic.

There is no reason to assume this article contains the entirety of the founder's knowledge about the topic. I for one think this write-up makes a much more compelling read than a comprehensive review of the academic literature. Of course, none of this prevents him from selling and marketing his product anyway...

[1] http://en.wikipedia.org/wiki/Power_nap#Benefits

This is a comment that often comes up when the sample size doesn't seem very big, but keep in mind that the required sample sizes to draw statistically significant conclusions can be surprisingly small especially when the effect size is large.

According to Figure 14 it seems to be the case, with the difference between the two group means being large enough to be significant at p < 0.002 (according to their numbers). A good threshold is usually considered to be < 0.05, so this is a pretty strong result. (The p-value is the probability this difference is simply a statistical fluke and not actually meaningful.)

Here [1] is a discussion on how to pick a good sample size for an experiment. As you can see in the table to the right, if the effect is strong a sample size of just a few dozens can be perfectly acceptable!

Here the biggest threat to the validity of these results is not the sample size, but whether one can generalize the case of the pilots in-flight (a very specific task performed by a very specific type of individuals). As trentmb says it's not clear whether pilots are very representative of the general population in this situation, although it also looks like there have been multiple studies done on the subject [2] which seem to confirm the benefits of napping as well. For what it's worth it definitely corroborates by own experience as well so I'm actually quite curious to see where Napwell will go.

[1] http://en.wikipedia.org/wiki/Sample_size_determination#Requi...

[2] http://en.wikipedia.org/wiki/Power_nap#Benefits

It looks like what they've done is more along the lines of finding a clever trick to improve the runtime performance of one of the common building blocks of a spell correction system (the part that given an input computes a set of candidate words that are close to it in terms of edit distance). It doesn't even seem to say anything about how to pick the best candidate once you've generated this set, so you can't really evaluate its accuracy as if it were a complete spell correction system. Norvig originally just used the straightforward "pick the most common word that has the smallest edit distance", but I didn't see them mention anything about any kind of strategy on their blog post.

Remember that both Easterlin's studies and the one in this article have been done in many countries and not just the US though. The $128k cap may seem limiting for the US but it is not for Nigeria or the other lower-income countries, yet they still show the same patterns.

This is precisely what Easterlin says: a relative increase in income has little effect on happiness past a certain point. This competing model (the one in the article) says that no, there is no saturation point and there is a logarithmic relationship between income and happiness where the effect of a %age change in income has a constant effect on happiness.

No, the models proposed by Easterlin is a fundamentally different model of happiness economics than the one proposed by the researchers in the article (I updated my comment to flesh this out a bit). Basically, Easterlin's research hints that happiness increases with income only at a cross-sectional level (by comparing different people at a given time) but not at the longitudinal level (the same people wrt to their changes in income). What I'm saying is that maybe the way the question is framed has a fundamental effect on the way people would rate their happiness: "I rate 7/10 in Happiness vs. I'm happy but less than if I made double the money".

This is one of the big controversies in happiness economics.

I wonder if this effect (which directly contradicts Easterlin's findings that money has no effect on happiness past a certain point; here, they contend that there is no saturation point and that happiness evolves with the logarithm of income) could be somewhat due to the way they framed the question: "assume you are on a ladder of happiness with 10 steps, which one would you say you are on; then tell us how much you earn". It is widely known in behavioral economics that framing effects can have a huge effect on the way people respond ([1] [2], and so on), so I wouldn't be surprised than the way you ask people to evaluate their own happiness could explain at least part of the difference.

One of the conclusions of the Easterlin Paradox is that people care more about how much they earn compared to their neighbors than the actual amount. I feel like asking the question this way (imagining their happiness as a ladder with 10 steps, then thinking about their income) would directly lead to people implicitly internalizing this comparison in some kind of mental model where higher wealth = more happiness because they're trying to imagine what the best life possible could be: "ah I'm pretty happy right now, but if I had a twice as much money I think I would be happier though, so surely I can't be at the last step at the ladder. Actually, people who have twice as much than that should be even happier, so I'll add some steps on top and say I'm a 6 right now".

This sounds plausible to me because while the authors conclude there is no saturation point where income doesn't bring more happiness, this is a scale from 1 to 10 so surely some people must rate themselves a 10. What would those who earn twice as much as them think then? This solution could be that "being on top of the ladder" in people's mind is somehow conflated with "being on top of the income distribution", with all the other levels being computed relatively to that. In other terms, this framing may incite people to evaluate their happiness on a cross-sectional level, with Easterlin's Paradox being precisely that the income-happiness relationship exists only at the cross-sectional level but not at the longitudinal level.

The debate between the two models (Easterlin vs. Stevenson and Wolfers) has been a longstanding debate in happiness economics, with both sides having confirmed their findings with multiple data sets [3]. Maybe they're both right in a sense and the answer just depends on which definition of happiness you're asking people to evaluate themselves with (relative vs. on an absolute level)?

[1] http://economistsview.typepad.com/economistsview/2006/08/the...

[2] http://www.adsavvy.org/the-power-of-framing-effects-and-othe...

[3] http://en.wikipedia.org/wiki/Easterlin_paradox

You're missing my point though. My point was not that opening links in a new window is always a good thing, just that usability experts keep parading the same old studies and scientific-sounding claims about "cognitive load" (and it's not just about this link issue) and that I was curious about how they were backing up their claims. Regardless of what I think the best behavior should be, as someone who cares about quality data and methodology I simply wished UX could be a little bit more rigorous, which is why I've been playing devil's advocate. Note that my original comment did not state any preference towards one side or the other (my last sentence even explicitly said so), I was just commenting on how I was curious to find more compelling arguments. If they were to say "it is the preferred convention because it seems reasonable and is consistent with our recommendations", that would be another story. But passing personal preference for scientific truth, and then using this as a pretext to be self-righteous about it (like the author of the linked post) is not OK.

My original argument was simple:

1) opening links in new windows is said to be bad because a) it breaks the back button, and b) the back button is the most important one

2) the back button does not seem to be as important as it is now because of multi-tabbed browsing. Furthermore, since what matters is not not the back button itself, but how users expect the back button to perform, the fact this functionality has become unreliable could change the user's expectations (it changed mine)

3) therefore, the original argument may not be relevant anymore

> Indeed. But chances are you wouldn't actually be measuring these things due to the huge bias involved in the measurement itself.

The burden of proof should be proportional to the size of the claims you make. You can only be as confident as your data: if you believe there are biases in the measurement, then you should stay measured, too.

By the way, you say:

> And that would qualify as a session that shouldn't be interrupted — i.e. it's a perfectly valid use-case, including for the OP.

Who defines what should and shouldn't be interrupted? In the case of an article, I could argue that when I click a link in the middle of an article (like in The Verge's case), it's generally just because I'm curious about the link, kind of like I would read a footnote in a book, but ultimately I don't want to lose my pace and that would interrupt my reading "session". It is definitely not an indisputable claim, but it sure is a justifiable one (unlike, say, auto-loading audio advertisements) so The Verge isn't evil for doing so. If they had an A/B test and it showed it increased retention and that this is worth irritating some users, that's their decision to make.

Anyway, I feel this discussion has grown way out of proportion to the original claim and that we're just arguing for the sake of being right at that point. I'll willingly concede that you're right to say that as of now, forcing new tabs may place an unnecessary burden on users using older hardware.

In this case: the federal government. The banks didn't randomly decide they were against marijuana, they're just reluctant because while marijuana is legal for medicinal or recreational use in a few states it's still a Schedule I drug at the federal level, which makes it legally tricky to handle the proceedings from the marijuana business.

> Not sure what the point would be…

"In God we trust, all others must bring data." Best practices should be grounded in data rather than opinions whenever possible, especially when they're based on claims about users' cognitive load like in the NN/g recommendations.

> Per parent, it gobbles RAM on mobile devices, and this leads other tabs to close prematurely. It also turns older devices into helicopters when the fan kicks in.

I don't find that to be true with mobile devices. I much prefer having my links on mobile opening in a new tab, because a) mobile internet connection can be unreliable (and often a much bigger problem than lack of RAM), so I may not still have reception when trying to reload the original page, b) slow page loads makes browsing not as enjoyable since transitions take time, so I'd rather have everything in separate tabs and c) being on the move means I often put my phone down to do something else, so I don't necessarily remember every tab's browsing history.

Besides, mobile browsers have gotten a lot better at managing RAM and most have been able to optimize background tabs for a long time, so I think the RAM issue is way overrated.

> Besides the offender's unwarranted sense of entitlement (by keeping you around against your will), the main issue is that it breaks the back button. 15 years later, it's still an unwarranted sense of entitlement, and it's still breaking the back button.

I can see several reasons except for "unwarranted sense of entitlement" for this practice. It's all about reasonable expectations on the users' end: if a user can reasonably expect the website will behave some way, then not doing it this way can be detrimental to him. For example, many people expect "help" links (like the one next to the HN comment box) to not make you leave the page and rely on the "back" function to restore your painfully typed comment once you realize it does. They may be wrong in expecting this, but this seems like a perfectly rational safeguard against accidental data loss, so going against this could very well "increase the user's cognitive load".

As for the breaking the back button, my previous point was that the back button is not as important anymore, in part because a) a lot of things break the back button because dynamic content has made it much easier to do so and b) multi-tabbed browsing is now widespread and users may not be as confused by the fact each window/tab has its own browsing history anymore.

There are plenty of contradicting effects (precisely the reason why you and I can legitimately feel different about this issue) and the point of doing an actual study is to be able to measure them so we can compare them and say which trade-offs are worth it and which aren't.

tl;dr: your snark is unwelcome

Are there any more recent studies with actual numbers and not just some vague talk about increased cognitive load (whatever this means)? Most I found seem to refer to the same 15 year old NN/g research report.

Since then a lot has changed, including the spread of multi-tabbed browsing (which one could imagine would have a huge impact on this issue) and drastic changes in the way web applications are designed. Is the "back" feature even still the most popular feature on a browser? While this claim would have been indisputable a few years ago, I seem to almost never use it these days unless I accidentally clicked on the wrong link. At least in my case, the evolutions I mentioned have changed the way I use my browser quite a lot. Less anecdotically, this does seem to be a more global trend since on Chrome for Android the back button has even been demoted to the "More" menu, while tab-switching has been given a more prominent spot (swipe from edge).

Not saying it has now become good to open links in new windows of course, but I'd be curious to see more recent research about the topic.

Thank you for the precision about Apple products. I may be wrong about the two finger gesture being disabled by default (edited my post to reflect that) -- it was my impression that it wasn't, but regardless I think we can agree it is not the most salient feature to new users. Using two fingers on the trackpad also means I cannot just reach out with my thumb to click but actually need to move my hand to perform the gesture.

My comment may have given the wrong impression -- I am not arguing that forcing links in new windows is a good thing, simply that it is not the anti-pattern people make it to be. In some cases like an app where accidentally leaving the page may lead to data loss or to a form resubmission, I actually think it's an acceptable trade-off and not an awful choice at all. I do agree with the author that in The Verge's case it isn't.

My comment was just based on the (totally subjective, of course) observation that to me that I tend to use a "open/close tabs" flow these days much more than "forward/backward in history", and that the "back" functionality seems less important than it used to be a few years ago because of changes in the way websites are designed.

Issues of choice aside (which seem to be your main grief; I have nothing to argue against it), the usability studies that condemn the practice tend use the fact that it disrupts the "back" functionality as one of their main arguments. My point being: if this functionality is not as important (as is the case for me), maybe this practice isn't so bad after all?

I used to agree with the author, but these days I find myself actually preferring having a link opening in a new tab, so I'm not actually that irritated when a page uses target="_blank" if it's somewhat justified (ie. if there's a reasonable expectation that I'll click the link as a temporary digression, before going back to the original page).

The problem is that sadly, closing a tab is often easier in practice than using the "back" functionality:

- many websites are poorly coded and break the "back" functionality, making it (sadly) unreliable. On pages that load content dynamically, results are not always predictable either

- my left hand is already positioned in such a way that hitting cmd/ctrl + w is trivial, whereas going back requires reaching all the way to the backspace button/the mouse/doing a multi-finger gesture on the trackpad

- if you had to submit content to get to the current page, usually going back will trigger a "confirm form resubmission" warning

- on mobile devices, the "back" functionality is not very prominently displayed. On Chrome, you have to click the "more" icon to access it

In addition, manually opening in a new tab (which requires right-clicking, middle-clicking, or ctrl/cmd + click) is not always as trivial as people imply:

- people who are using a trackpad do not have a middle button

- right-clicking is has not been part of Apple's design for a long time. You can perform them using cmd + click or using two fingers on the trackpad (I believe it is disabled by default), but it's not as convenient

- On a MacBook, the modifier keys (fn/control/option/command) are all placed next to each other and it's not always obvious which one does what. It's easy to get confused or to accidentally hit the wrong one. I've personally done option + click by mistake countless times, which opens a prompt to save the link, and it's always pretty frustrating

- the right-click equivalent on touch screens (long press) is a bit clunky

And this is coming from a tech-savvy user who actually knows about these options -- you'd be surprised at how many people don't. Of course, having the ability to make the decision is important for power users, but I can't help but wonder if for less sophisticated users the practice is not so bad after all. The usability studies I could find are pretty dated and I would not be surprised that usage patterns have changed.

This is called ad retargeting -- the basic premise being that conversion rates are much higher for items the user has actually looked at in the past. Usually it's only supposed to show abandoned purchases, but sometimes it doesn't work and shows you stuff you already bought. I personally feel retargeting to be a bit too intrusive for my tastes but the conversion numbers are excellent, which is why this industry has boomed in recent years. It looks like your browser's incognito mode can be useful for online gift shopping after all!

There are a few companies who do this like Criteo or Adroll, but I believe Amazon is using Triggit [1]. It looks like it's working for them: http://marketingland.com/triggit-facebook-exchange-36-better...

[1] http://blog.triggit.com/amazon-chooses-triggit%E2%80%99s-dem...

I initially had the same reaction as you, but reading the discussion between the author and Telegram in the comments (both on the linked article and the original HN thread) it seems to be this is largely deserved given the way Telegram has been responding. They've essentially refused to justify any any of their (curious) choices and relying on authority arguments instead:

> We grew tired of “experts” too lazy to read the full documentation.

It's quite sad that this post is even necessary. That said, having a proper training/cross-validation/validation setup is sometimes not that obvious, as you have to stop and think about possible sources of contamination -- some sampling biases, for instance, can be quite tricky to detect, or your algorithm design might be flawed in some subtle way.

Personally, I wish people emphasized more the importance of a general understanding of econometrics when doing machine learning. In most of the introductory courses I've seen, the link between both field is never made explicit, despite the obvious analogies (coincidentally, there was an article by Hal Varian on the front page two days ago that discussed how both fields could benefit from sharing insights [1]). Understanding the idea behind minimizing generalization error is one thing, but I find that thinking in terms of internal/external validity and experiment design often gives people a more intuitive understanding of validation procedures, both regarding why and how we should do it. The same goes for understanding effect size, confidence intervals, causality (and causality inference), and so on.

[1] https://news.ycombinator.com/item?id=6870387

True, but intuition and general analytical ability is often overlooked when hiring data scientists -- because the term is so broad, what people are often looking for is a mixture of statistical know-how and programming ability, but often forget to ask for a good understanding of econometric principles.

For instance, there is a difference between understanding generalization error in the statistical/machine learning sense, and generalization error in the sense of external validity. You'd be surprised at how many models, even at reputed companies, use features that do not make sense or are based on implicit assumptions about the studied population. Obviously insight is always a good quality to have, but it is particularly critical for data scientists as the right or the wrong insight in the context of machine learning algorithms can have huge consequences on your company.

On a semi-humoristic note, there's also John Perry's Structured Procrastination theory, which won him the 2013 Ig Nobel prize in literature: http://www.structuredprocrastination.com/

Basically, be productive by doing important things as a way to procrastinate on even more important things. He wrote it as a humoristic essay but I actually find one of the tips quite useful: instead of trying to beat procrastination by taking on less responsibilities in the hope you'll finally be able to uphold them all, take on more tasks so that even when you'll inevitably fail to do some of them, you'll still have achieved much more than if had challenged yourself less in the first place.

The fact you use Jesse Owen's example is a bit ironic, since he was actually much better treated in Germany than in the United States where racial segregation was still the norm. By his own account: "Hitler didn't snub me – it was FDR who snubbed me. The president didn't even send me a telegram."

(Not making a point, just remarking.)

> Could you imagine what was going through Adolf Hitler's mind when he saw Jeese Owens during the 1936 Olympics?

For the curious, we actually know what Hitler's reaction was. This is how Albert Speer, who was in the box with him at the time, described it:

"He was highly annoyed by the series of triumphs by the marvelous colored American runner, Jesse Owens. People whose antecedents came from the jungle were primitive, Hitler said with a shrug; their physiques were stronger than those of civilized whites and hence should be excluded from future games." [Inside the Third Reich, 1970]