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I see. "Men and/or fuckable" then

I really did not mean to be insulting. I am just saying chart makers can choose to make a zoom in, and it is not automatically propaganda or something. All this has led people astray of the real issues, like WTF is measuring 'happiness' on a 1-10 scale, and what are the metric properties of this 1-10 scale. Then there are all the sampling issues and what have you. I just expected more people discussing this stuff rather than the Y-axis.

Oh sport, and I thought I was the one beating on a dead horse here. I understand why people claim to take issue with the Y-axis range. I am just saying chart makers can zoom in to make a point, and it is not automatically misleading. That is all. Anyway, thanks for writing this. Looks like a lot of effort, and some of it will make sense in my stats coursework, thanks!

And as I read some where here, if testosterone levels is unfair advantage why aren't there limits in the men's league too? It is so just they police women bodies (cis and trans alike). Here is the original comment but I did not record the username, so sadly I can't credit them

If testosterone is a PED and it doesn’t matter if the athlete is cis or not, then there should be a hard limit for both male and female athletes to ensure fairness. If too much testosterone is only a problem for women then clearly it’s a sexist attempt to police women’s bodies. Every human body produces some amount of testosterone, either too much is an unfair advantage or it isn’t.

Yes, we were expecting a clue that transphobe halfwits are ignorant. Can they even define what trans is? I don't think so.

Are you forgetting the whole subculture of "transvestigation"? They were the Q-anon conspiracy theorists before Q-anon, and even Michelle Obama was claimed to be trans by this lot.

Wasn't this was the Ancient Greek version of gender?

This is indeed misleading. It has no numerical figures, and it wastes loads of ink and screen space. The other one is better structured as a chart. I a sorry you spent your time to demonstrate something we all know, but may be Excel has good reasons that cuts off the axis at 6.

Although there is a common tip in critical thinking classes that manipulating the Y-axis range can lead to misleading presentation of a difference, I believe in this particular graph, which clearly provides numbers to compare, you can't say it is misleading.

People can read and compare the values and draw their own conclusions. And I am saying that without any consideration of the distros discussed, since I am impartial to distros, I like all distros I have tried.

This "study" almost certainly must have way deeper assumptions- and metrics- related problems to start with, so even finding myself having this argument is preposterous. But I am just pointing out the misapplication of critical thinking guideline, and this is a valid point which I insist everyone who relies on to consider, if you care about critical thinking at all.

No one said you are doing layman statistics, the pasted comment is from another discussion, provided here for context, and for very good reasons. It aligns with obvious misconceptions about statistics that should be pointed out. Probability and statistics are thorny subjects that nonetheless are inevitable in order to understand the world surrounding us, material, social, and economic, so yes I will nitpick here and call out the misapplication of canned critical thinking thought-terminating cliches.

This sounds valid. I wonder how many Scandinavians switched to Linux because of Windows 11.

Fair. You know these figures right out from the graph don't you?

Ah the statistical significance, which as everybody knows is assessed ...visually? Mic drop

BTW I have another comment here, totally irrelevant to this discussion, that I bring up statistical siGnifiCAnsE as an example of confident falsehood. Thanks for proving me right lol

Edit: here it is for context ( from https://lemmy.ml/post/17638298/12096466 )

Layman statistics is not the hill I would die on. Otherwise (being guilty of the fallacy myself) I now think that making a subject mandatory school lesson will only make people more confidently incorrect about it, so this is another hill I won’t die on for probability and statistics. See for instance the widespread erroneous layman use of “statistical significance” (like “your sample of partners is not statistical significant”) you see it is a lost cause. They misinterpret it because they were taught it. Also professionals have been taught it and mess it up more than regularly to the point we can’t trust studies or sth any more. So the solution you suggest is teach more of it? Sounds a bit like the war on drugs.