[TangoTrotFox]

>"I think when statistics is involved, the results are inherently untrustworthy. This is not really surprising because there is a whole bunch of ways these studies that involve statistics could go wrong. And we are still finding new ways on how this could go wrong."

Another very real issue here is that malicious use of statistics can be used to show nearly anything in ways that can be extremely difficult to detect, even when the maliciousness is hidden in plain sight. And then going a step beyond that there's plain old number fudging which is almost impossible to prove since variance works as sufficient plausible deniability. And finally there is of course plain old ineptitude. Like you mention even when trying to do things completely by the book, statistics are incredibly difficult to get right.

Something that comes to mind here is the recent MIT study stating that Uber drivers earned $3.37/hour. That study was completely broken. [1] It's debatable whether the cause was maliciousness or ineptitude, but the point is that these problems arise, with a disturbing regularity, even when the most reputable of names are attached to them.

[1] - https://qz.com/1222744/mits-uber-study-couldnt-possibly-have...

[AnimalMuppet]

Feynmann said, "The first rule is that you must not fool yourself. And you are the easiest person to fool."

There can be malice, sure. But there can also be desire to believe. And, hey, here's a statistical analysis that shows what the investigator is already biased to believe anyway...