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One way people try to tease out those differences is through methods like "Difference in Differences"[1] which try to estimate causal relationships from observational data. These methods are used in marketing analysis as well.

In my experience, it is easy to break one of the many assumptions inherent in methods like Diff-in-diff. Because of this I have little trust in these techniques in general.

[1] https://en.m.wikipedia.org/wiki/Difference_in_differences

One small additional point. I completely agree that Jagex has done a great job maintaining OSRS. Polls for changes to OSRS typically require 70% of votes to pass[1] instead of a simple majority. This is part of the reason why it is difficult to get major changes like new skills added to the game.

As a long-time player, I really enjoy the conservatism this leads to in the evolution of the game. It is great to be able to pick up my character after a year or two off and have a very similar experience (+/- a few quality of life updates I'm likely to appreciate).

[1] https://oldschool.runescape.wiki/w/Polls

You're correct. I was saying that correlation implied either causation or at least a common cause, and you correctly point out that there can be (edit: and frequently are) spurious correlations. The desire to see causal effects is strong in us humans, and it is easy for us, me especially, to fall prey to this logical fallacy.

For people who would like to see a demonstration of the effect yolo69420 is pointing out, you can visit the website below [1]. It, among other things, shows how Nicholas Cage movies are correlated with swimming pool drownings.

I completely agree that the Twitter post does not prove there is a direct causal relationship between the maps they compare, nor even that there exists a common cause. I would contend that this is a very high standard to hold for interesting content on the internet. If you would like to hold to this standard, you will likely come to more robust and defensible conclusions than myself.

I find it fun to speculate on possible common causes. If I had any actual ability to change things based on my conclusions, I'd likely increase my burden of proof to a much higher level like you suggest.

[1] http://www.tylervigen.com/spurious-correlations

I completely understand your point. Misinterpreting correlation with causation is something that frequently bothers me in writings and discussions. In this case, however, I did find the correlations the author pointed out interesting. I did not interpret this as causal (the author may have made that claim, but I was more interested in the maps).

I still found it really cool to see how much an impact geography and path dependence has on our current state. I may be over generous, but when they show maps like the Alabama one where an ancient sediment deposit is correlated with farm size, racial makeup, and election results I think they are giving an example of how there can be common causes tied to geographies over long periods of time.

You're completely correct that simply overlaying the Austrian Empire's borders on a map of Romania's election results does not prove a causal link. It is much more likely that there is an underlying common cause (geographic feature, ethnic makeup, etc.). Pointing out these correlations is fun to me, as I'm able to speculate on the possible common causes.

I believe this is in reference to Professional Engineering firms, which often requires PEs either as owners or in certain roles. As far as I'm aware software engineers are not required to be Professional Engineers in the US for most tasks, nor are SaaS shops required to be licensed as Engineering firms.

[1] https://www.harborcompliance.com/information/engineering-fir...

I find it fascinating that there are more than 11,000 tax jurisdictions in the USA[0]. I think the comparison is interesting, as I'm sure many of these are ignored by many online retailers. It seems like there are some efforts at standardizing Sales Tax approaches across the country. Similar efforts could be interesting for consumer protections.

[0] https://taxfoundation.org/state-sales-tax-jurisdictions-in-t...

I found myself struggling with the intuition of this similarly to amingilani until I made the connection you're mentioning to infinity. The thing that helped me understand the fallacy was understanding how truly large infinity is. If you've seen 10 coin flips, or even 10,000 or 10,000,000, those are all effectively nothing when compared against infinity. If you know ahead of time that a coin is fair (so you're not trying to test this hypothesis), you gain zero information about the long-term behavior of the coin from any finite number of flips.

As you mentioned, you don't see the convergence to 50% with any finite sample size, because that behavior is only guaranteed at infinity. All this to say, infinities are weird. 10,000,000 + infinity exactly equals infinity.

This isn't quite what you said, as your comment spoke about the energy industry specifically, but I decided to see if there was any data on people's beliefs about climate change by state. I found this interesting site from a program on Climate Change Communication from Yale, and it allows you to view the results on various questions related to climate change by state. My conclusion from clicking through a few of these is that Texas is close to the national average in climate change beliefs.

Some numbers: Global warming happening 71% (-1 from Avg), Caused by humans 56% (-1 from Avg), Support regulating CO2 72% (-3 from Avg), Expand offshore drilling 57% (+5 from Avg)

https://climatecommunication.yale.edu/visualizations-data/yc...

I think you've hit on what always bothers me about this sentiment. It is obvious that at any point in time you can charge the maximum customers are willing to pay, but that allows for disruption through the channels like competition. The opposite where you charge the minimum to continue providing the goods or services seems optimal, though, leads to a company with zero profits that is unattractive to investment. Is there any literature on how to identify the optimal point of "whatever customers are willing to reasonably happily pay"? Businesses successfully exist on many points in the spectrum of zero profits to most profits the market will bear, but I'd be interested in anything discussing optimality.

[Edit] Amazon employee working in Physical Consumer (not AWS). Asking out of personal curiosity.

I somewhat disagree with the idea that a Big Corp reduces your learning opportunity. I work for one of the big companies, and one benefit I don't see highlighted frequently is changing specialties. I have worked in 4 different job families over 6 years. If you do work for a Big Corp and you're an effective employee, you can pretty easily work on jobs at the border between the job you have and the job you want. This may be specific to my employer, but I've been able to find ways to demonstrate my (on the job learned) knowledge in a field and get a job I find interesting.

Current Amazonian, my opinions are my own.

I love the emphasis on writing these papers to drive a meeting, and 6 pages is an upper limit. I personally prefer trying to condense it to 1 page. I will sometimes need get Product, Tech, and Ops to agree on something, and I find writing the paper really helps me solidify my argument. If you're just trying to get your team and principal engineer to agree to a design, however, the 1 page technical doc you mentioned is sufficient. Full 6-pagers are more common when working across orgs, in my experience.

I'm no expert, but Wealthfront currently uses VEA for foreign stocks and VWO for emerging markets.

https://support.wealthfront.com/hc/en-us/articles/210999343-...

This appears to be another scalability vs human intervention argument that occurs commonly in public and private enterprises. I think much of this community favors the scalability side, but forgets that humans are available to provide better solutions in almost all areas that are currently available to computers.

I really appreciate the cognitive dissonance you're experiencing related to this case. Blindly accepting presumption of innocence, which I support in the justice system, is not something people typically do. This situation seems similar to the idea of jury nullification, which the article mentioned. If you choose not to help because you disagree with potentially helping the system make the wrong choice, I would support it for the same reason we choose juries. In the existing American justice system, the primary reason for juries is to have peers not ingrained in the system making judgement calls on the evidence they have.

I have to say, I strongly disagree on this point. I am a coder who works in a variety of languages build on many paradigms, of which SQL is one of my most enjoyable. I agree that the creation of schemas can be painful, but SQL's almost Prolog level of declaration can be beautiful in certain problem spaces. It is unfortunate that the current state of query optimizers leads to leaky abstractions where one must rearrange queries to allow for efficient execution. Still, I have had a great deal of success introducing SQL to otherwise nontechnical people, and they also love the fact that one can describe the solution you desire as opposed to instructing the computer on how to get there. These people particularly benefit from the almost English nature of the language, and I feel I have no right to complain about any syntax with a `use Perl;' background on my desktop.

I think this is okay, but I really hate the current landing page. It would be nice to have a description of the service instead of a message warning you that you are not logged in. Seeing that message I almost went to do something else because it seemed so off-putting. The service itself is oddly addictive however, so long as you remember that your product is entirely driven by your community (which you are probably well aware of). Other than that, I think I could see myself flipping through random status updates on occasion.

Both of those languages have seen vast improvements in speed throughout the past ten years. Java 1.4.2 was immensely faster than any previous Java implementation. I would be very interested in seeing this study redone with the newest Java, Python, Ruby, and something Lispy.