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submitted 1 day ago by fossilesque@mander.xyz to c/science_memes@mander.xyz

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[-] edinbruh@feddit.it 25 points 1 day ago

Say no to statistics altogether. If we form a compact front, we can eradicate the disease of statistics from the face of the earth.

As motivation, I'll explain why statistics is only good for stealing:

Statistics is used to invest in the stock market, which is stealing by definition
Statistics is the foundation of modern AI, which as of now is mostly used for stealing work and intellectual property
There is no real statistical research, but every other paper is forced to have a little useless graph and a p-value made by some statistician, who steals fame from the real researchers who made the rest of the paper
Statistics is at the core of the gambling industry, which preys and steals from the elderly and economically weak
Every fucking formula for calculating probability needs to have a "mathematician's" name even if it's always sums and scaling that a toddler could come up with. Remembering those names steals neurons from students
Etcetera

[-] angrystego@lemmy.world 6 points 16 hours ago

Oh, they played us for absolute fools!

[-] wolframhydroxide@sh.itjust.works 9 points 21 hours ago* (last edited 20 hours ago)

Quality shitpost, but the naming thing is true of virtually everything in mathematics, with good reason, because otherwise you'd just be talking about "that slightly different combination of arbitrary letters by which we do something very similar to, but measurably distinct from, the use cases of the other three equations like it".

See:

Pythagorean theorem (geometry)
Dijkstra's Algorithm (graph theory)
Fermat's last theorem (number theory)
Peano axioms (formal logic)
For that matter, the word "Algorithm" comes from the Latinised name of the dude who invented algebra, and the word "algebra" is just an overly truncated version of the title of that dude's book.

This is also doubly true in science, where there are 5000 different "laws" and "theorems" surrounding something like gas behaviour, so at some point, you have to differentiate them based on their history, rather than what they do. Hence "Charles' law", "Boyle's law", "Gay-Lussac's law", "Bernoulli's principle", the "navier-stokes theorem", "rayleigh-benard convection", etc...

[-] edinbruh@feddit.it 3 points 20 hours ago

I'll admit that was a bit of a stretch. But I also think the naming thing is a problem. Especially in mathematics, even when it is not named after a person, you often have no clue about what it is from just the name (i.e. what do you think is a magma in mathematics?)

[-] wolframhydroxide@sh.itjust.works 3 points 20 hours ago* (last edited 20 hours ago)

I believe that they contribute to understanding, because human minds are wired to engage with stories. If your chemistry teacher was worth their salt, they'd teach you Gay-Lussac's law by telling you about how, when the hot air balloon was first invented, Gay-Lussac was seen as a mad young upstart by all of the older scientists for wanting to go up in one. Well, not only did he nearly die making measurements, he also showed that, at higher altitudes, there was lower pressure and lower temperature. Then, your chemistry teacher should pull out a spray-can of keyboard cleaner, invert it, spray the liquid into a beaker, and let everyone feel the adiabatic temperature depression from expansion (of course, most of the endothermicity is from the boiling of the liquid, but the point stands) they can explain that any compressed gas gets colder when you release it, whether the keyboard cleaner, spray paint, or the compressed coolant in the coils of your refrigerator. Lower pressure, lower temperature. Gay-Lussac's law. Now, all of those students will, when they think about the relationship of pressure and temperature, remember Gay-Lussac in a hot air balloon, at low air pressure, and low temperature.

[-] edinbruh@feddit.it 3 points 20 hours ago

Now that I think about it, I think my teacher called it just "lussac's law" because you cannot pronounce "Gay-Lussac" in front of a classroom of 14 year old boys. I guess you are right about the stories, but I'm not sure the name actually helps with that

[-] chgxvjh@hexbear.net 3 points 1 day ago

Is this a shit post?

[-] edinbruh@feddit.it 4 points 1 day ago

No, it's my belief. I was forced to do statistics at school from a young age, and it polarized me.

It all started in kindergarten, when the teacher wanted us to take polls of stuff like favourite colours and such, and find the mode of the polls, and I didn't want to pay attention to other kids' favourite colours so mine were always wrong.

Then it continued through elementary, middle, and high school, and I often failed statistics tests, because they always had you calculate ludicrous amounts of differences and squares and means and I would inevitably make mistakes. My maths average was 9/10 regardless, but I hated statistics.

Then I had to take a statistics exam for my bachelor degree in computer science, and I failed and had to retake it next year.

Then I had to take a second statistics exam for my master's degree in computer science that I'm pursuing right now. And I failed that and had to retake it.

And this is how I specialised in formal verification and abstract interpretation. Many such cases.

[-] chgxvjh@hexbear.net 2 points 1 day ago

Not gonna lie sounds like a skill issue.

There are do many situations where it's either statistics or just vibes/gut feeling. And I'd prefer it to be statistics if it's remotely important.

Of course there is plenty nonsense one can do with statistics and statistics without transparent methodology are a great way to hide lies.

[-] edinbruh@feddit.it 3 points 1 day ago

Hey, in the end I got 28/30, I didn't just barely pass the exam. It just sucks because I don't like it and don't want to study or know about it. Also there is a lot of gut feelings involved in statistics. Don't pretend it's like an exact science or something. You make your calculations and it spits out a number and you go like "hmmmm I do not vibe with this number. This stuff feels more important so I want a better number" the calculations themselves involve a lot of "hmm this data feels like it benefits from this approach"