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.
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).
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.
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.
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.
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.
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