I told a guy that a wide variance in data essentially means that results were random then he proceeded to explain p values and I’m like “yeah I’m sure the random values values came from nature”.
Moral is p values kinda worth less than variance
Are you saying you can’t determine a difference in aggregate statistics by performing more trials if the variance is high?
You can the issue with A-B comparison is that is kinda expected for one group to be higher on average simple based on the data points you selected.
If the averages are kinda similar and variance are high in both group A and B then I’d say both groups are statistically the same even if the statistical values are different
So you have two groups of ten experiments, mean if group A is 100, mean of group B is 105, variance is 25 (for both groups). Obviously we are not confident that these groups differ.
Now suppose we repeat the experiment two billion times. The group A average is now 99, and the group B average is now 103. The variance is still 25. Are you still not confident that the groups are different?
Is this a Bayeskisser meme? 😛️
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
Oh, they played us for absolute fools!
Is this a shit post?
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.
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.
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…
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?)
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.
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
Xkcd 1132

I noticed that Soviet textbooks were frequentist e.g. Khintchin, while modern textbook by Murphy is Bayesian. The frequentist approach makes more sense to me.






