Of course it's social "sciences".
Also medical treatment: https://news.ycombinator.com/item?id=10387375
Twenty-nine teams use same dataset, find contradicting results [pdf]
31–36 of 36 posts
Re: Twenty-nine teams use same dataset, find contradicting results [pdf]
#32Earlier quoted context omitted.
How do you see it as derogatory? I'm a native English speaker and have never thought of it that way. I didn't click the link, but did appreciate his short summary – and upvoted him for it. ;)
'tl;dr' is often a troll response to a long post that that someone has obviously spent a lot of time on. Bonus troll-points if the long post was in response to another troll. Example: poster1: only retards use vi, notepad rules poster2: huge list of reasons why vi is better than notepad poster1: lol tldr
I was quite peeved when I first saw a "tl;dr" comment concerning one of my blog posts. My thought was, and still is somewhat, "if you didn't read it, how can you say it was too long for what it needed to cover? Why do you feel the need to tell others that you have the attention span of a fly?"
We already have terms like "summary", "digest", and even "précis"; why create a new term imbued with snark?
Re: Twenty-nine teams use same dataset, find contradicting results [pdf]
#33Serious question - what if players of a certain skin color break the rules more frequently than another skin color? "Bias" is extremely subjective and complex. Was this possibility taken into account?
Re: Twenty-nine teams use same dataset, find contradicting results [pdf]
#34I understand how tempting it is in our age of big data and all that stuff to perceive this as some curious new phenomena, but it really is not. This is precisely the reason why we've come up with some criteria for "science" quite a while ago. And in fact, all this experiment is pretty meaningless. So, for starters: 29 students get the same question on the math/physics/chemistry exam and give 29 different answers. Bre…
Your rant makes no sense. I flip a coin 100 times and it comes up tails 99 times. You are basically saying that asking "Is the coin more likely to come up tails" isn't a real scientific question. That's just silly.
But the coin doesn't have free will like the players. Some players may prefer heads over tails.
Re: Twenty-nine teams use same dataset, find contradicting results [pdf]
#35Earlier quoted context omitted.
The blog post is a great overview as well as useful context, thanks for sharing it. TL:DR summary: Scientific results are highly contingent on subjective decisions at the analysis stage. Different (well-founded) data analysis techniques on a fairly simple and well-defined problem can give radically different results. It's very interesting research -- a great real-life example supporting the models Scott Page et. al.…
Off-topic, but you seem well positioned to answer: Why do you say "TL:DR" here when summarizing a short blog post that you enjoyed? Clearly the meaning has diverged from the original abbreviated insult of "Too long; didn't read", but I don't understand what people mean when they use it today. Why did you phrase it this way? Are you a native English speaker? If not intended to be derogatory, does the dissonance bother…
> I don't understand what people mean when they use it today
By now, it often is used to be friendly. There's a subconscious acknowledgement that long words take people's time. The speaker can even be talking about his own work and tell everyone "tldr version: " at the top.
Google uses it a lot in their own docs: https://developers.google.com/s/results/?q=tldr
You can also choose to pronounce it "teal deer" and use images of a green deer animal to signify the same.
...
In some situations, if you want, you can say it to be mean.
Re: Twenty-nine teams use same dataset, find contradicting results [pdf]
#36Earlier quoted context omitted.
There are three kinds of lies. There are also three kinds of comments I see in this thread: > "This is interesting, here's some thoughts and ideas that further contribute to this subject" > "This is interesting, here's a link to some further writing on this subject" > "The entire concept and discipline of statistics is bullshit." Par for the course here at Hacker News.
Hey, the null hypothesis is powerful and valuable. I, for one, and happy that all three types are well-represented; all three are healthy in moderation. I also think that the quote fits in quite nicely here, it's not a wholesale rejection of statistics.
The quote itself isn't, but just posting a link to the Wikipedia article without explaining how they think it applies here is pretty much a wholesale rejection of statistics.