The entire point was that the metrics I chose were bad. Furthermore they were such minor differences that even if they weren't bad they still wouldn't be relevant. They were intended to be comically useless.
It means that the hypothetical author of the article didn't have any idea what they're reporting, which is exactly what I was trying to express. The authors rely on the readers' ignorance and the way many people reflexively accept numeric data as true, pertinent, and sufficient evidence of any claim.
If you actually read the article, why would you choose an irrelevant metric that is basically uncorrelated with the actual content of the article to prove your point?
That’s what the person you were responding to was saying- that they were surprised at the difference between their anecdata and the real data. And you responded by shitting on them for no good reason. Great job.
Thanks for trying to explain your position. I don't have the facts myself. Perhaps you could give a specific example of which data in the article were incorrect. Also, I would be pleased to know how you were able to discern the motivation behind the supposed mistake(s) made in the article.
Yes, arithmetic means are inherently misleading and everyone knows that. They summarize a quantity of information and conceal its important attributes like variance and skew.
The 7.7 figure was probably not being used to deliberately mislead.
The complainer hadn't in fact fact mislead; they had access to other data from the paper on which to base the complaint.
Basically it boils down to "you shouldn't have summarized such and such data using an arithmetic mean because I don't like means; whenever someone uses a mean, they are trying to deceive".
But the thrust of my message was about the misunderstanding of statistics, so the actual numbers (correct or otherwise) are irrelevant to the point I was making. Replace the numbers in my comment with the correct ones and the meaning remains the same.
I think the actual number is not the point of the article, exactly. The author is trying to point out that the method is flawed, and statistics is much more complicated than anyone one number from one source.
I didn't call the results "crap". I am simply pointing out that they are meaningless without knowing the methodology behind them. (And we aren't just missing the "perfect details of everything" here. As far as I can see, we have no rigorous details whatsoever.)
I would remind you that you were the person who was attacking another poster's position based on your interpretation of those currently meaningless numbers. It's up to you to back up your claim, not up to the rest of us to figure out whether your argument has any merit.
For most purposes, yes. But the author called out news reporting that quotes these "stats". Its important for journalists to understand the differences.
You're rejecting this article, and the entire publication because it doesn't confirm your current understanding? You're suggesting to switch away from common metrics because they don't provide the answer you expected?
That strategy won't get you far.
Of course, one article is a drop in the bucket. But take it for what it is, not reject it because it doesn't follow the narrative you have. People like the narrative of generational politics that is currently popular, but that's probably because it gives them something to blame that's easy to point at... yet the plot holes are massive and obvious when you open your eyes to them.
Yes we all know it's possible to lie with statistics. What are your criticisms of this article in particular? If you don't have any then you're just baselessly casting aspersions.
It means that the hypothetical author of the article didn't have any idea what they're reporting, which is exactly what I was trying to express. The authors rely on the readers' ignorance and the way many people reflexively accept numeric data as true, pertinent, and sufficient evidence of any claim.
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