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To: cgbg

You are one smart cookie. I mean that sincerely. Yes, hence the axiom “correlation does not equal causation”. Studies that look at correlation can be helpful insofar as they might point to an need for further research, though.

For example, if outbreaks of a particular tick-borne disease occur only or mainly where a certain species of mammal is found, that mammal may or may not be a natural reservoir. This correlation does point to the plausible reason for further investigation, though. Researchers go into the field, collect and test these mammals, and find they indeed carry the disease and are also infested with the same species of tick already known to carry the disease. Bingo. Or not — then start over and look for another species.

Proper studies looking at correlation plainly state they prove nothing but only point to a potentially promising area for further research.

Yes, you know what they say about “lies, d*** lies and statistics”. Amateurs and fraudsters using creative math (or faulty data) can sure churn out some whoppers! Even professionals sometimes err. That’s why it’s so important to scrutinize such studies. Statistical analysis can be very useful when properly applied to proper data sets. Otherwise, GIGO. And there’s lots of that floating around the web.

I always approach a study with skepticism, even if it’s in a reputable journal. Everyone should. Some check out, others don’t, while still others point to as-yet-unproven possibilities.


131 posted on 09/01/2022 8:25:12 AM PDT by CatHerd (Whoever said "All's fair in love and war" probably never participated in either.)
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To: CatHerd

Thanks.

I think this is a good example of where the “peer review” model for academic review fails.

The “peers” accept the same low standard for statistical analysis that they use—nobody wants to “blow the whistle” on the practice since it could blow-back on them.


132 posted on 09/01/2022 8:28:08 AM PDT by cgbg (Claiming that laws and regs that limit “hate speech” stop freedom of speech is “hate speech”.)
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To: CatHerd
Yes, you know what they say about “lies, d*** lies and statistics”. Amateurs and fraudsters using creative math (or faulty data) can sure churn out some whoppers! Even professionals sometimes err. That’s why it’s so important to scrutinize such studies. Statistical analysis can be very useful when properly applied to proper data sets. Otherwise, GIGO. And there’s lots of that floating around the web.

I don't see you even mildly warning about the new Omicron jabs, even though they haven't been through any human trials, and have been tested on eight (yes, as in 7+1) mice.

Tell me what kind of meaningful error bars you expect out of that, to justify giving a jab to millions of people, for something that even your fellow trolls, like David UnChased, say is not a concern anymore.

Troll.

183 posted on 09/01/2022 10:46:04 AM PDT by grey_whiskers (The opinions are solely those of the author and are subject to change without notice.)
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