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I don't know, but one of these two things is not a useful metric for what this article is trying to claim.


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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.


I don't see how the article's data supports the headline at all.

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?

I don't believe that article is accurate. It's more like some guy's biased opinion than a serious quantitative analysis.

The source article that the OP is based on doesn't provide the numbers that the OP claims it does.

That doesn't seem to be a very informative statistic, either way.

The article made a claim. Im pointing out that it doesnt fit the given data.

Those are extremely arbitrary metrics stated without sources. Do better.

That's not really how such statistics are useful.

What's your point? Those two numbers do not directly correlate.

That seems to be what the data is saying. I think the article is trying to paint it differently and they don't actually understand the data.

See the comments for the article. The numbers used are so far off that they are meaningless.

The article ignores the data.

I realize it's just a blog post and not a scientific paper, but the author didn't even cite a source for that statistic. My gut reaction is that it's probably incredibly misleading if not outright false.

It’s a reasonable assertion, but it’s not backed up by any figures that I can imagine.

That article gave no numbers. It made a claim and didn't back it up.

I am positive there's some sort of problem with these numbers and a major false comparison going on, but this doesn't seem fair either way.

I don't see any reason to believe that the numbers in that infographic might be accurate.

I've taken a look at the statistics presented here and mathematically that conclusion is not supported.
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