>Personally I wouldn't trust a stastical model from someone who advertises that they own the book "how to lie with statistics" and obviously used it

why?

Yep, and it's a suspect one at best. Personally I wouldn't trust a stastical model from someone who advertises that they own the book "how to lie with statistics" and obviously used it

The mean is what is often meant by the term but not always. "How to lie with statistics" is a great book and I highly recommend it to anyone still confused by such terms -- or anyone who ever sees, say, ads.

"There are three kinds of lies: Lies, damn lies and statistics" -- Mark Twain

Darrell Huff - How To Lie With Statistics[0]. And the first chapter or two of David Spiegelhalter - The Art of Statistics[1] has a good example of absolute vs relative rates/probabilities with respect to medicine. Pretty basic an important issue to understand.

[0] https://www.goodreads.com/book/show/51291.How_to_Lie_with_St...
[1] https://www.goodreads.com/book/show/43722897-the-art-of-stat...

The book "how to lie with statistics" (1954) was written before tags like /s were invented. Referencing "how to lie with statistics" is an indicator that the author is trying to avoid common pitfalls in statistical reasoning.

I own an inherited blue Pelican paperbook copy from my pharmacist grandfather.

https://en.wikipedia.org/wiki/How_to_Lie_with_Statistics

This guy has read "How to lie with statistics".

A major investor & leader in healthcare that shall remain unnamed had a book "How to Lie with Statistics" in a public reading list. It's a good book & a quick read. Highly recommended.

It's interesting that it takes an editorial to make people suspicious of statistics, how statistics can be abused, & the conflicts of interests that many people who utilize statistics have. Sample bias needs to be treated as deliberate dishonesty rather than a simple mistake. These people who make these mistakes are professionals and should know better. Their code of conduct should penalize them harshly for making these sort of mistakes.

A strict code of conduct with harsh professional penalties are necessary to remove bad actors who hide behind subtle lies that have a major impact on public policy & public opinion. A slap on the wrist means it's always worthwhile to lie with statistics. A removal of license & banishment from the profession on the 1st or 2nd offense would quickly remove the bad actors. This code of conduct should also extend to the peer review process. If the peers pass bad statistics, the peers need to be held accountable as well.

Your comment starts with a disingenuous sentence, and continues to show a level of bitterness I've seen before in people who believe themselves to be more knowledgeable/experienced than their surroundings (or they actually are), but never got a chance (or so they believe).

I didn't claim to know everything there is to know about statistics and research in general, but I think I know enough to tell that this is not a study, but a marketing campaign for whatever this usehaystack thing is.

> First, they should have tried to poll around 400 people (and perhaps they did!),

If you had read the article, you would have known that that's not what they did.

> By typical polling standards (95% confidence interval, random sample from filtered population), we expect that 77-89% of UK software developers are actually burnt out. That is still three out of every four people in the industry!

Do I understand correctly that you've worked on this? That certainly explains the hostility, but nevertheless.

> we expect that 77-89% of UK software developers are actually burnt out.

That's not what the link/study says.

> That is still three out of every four people in the industry!

This is absolutely wrong, without a shred of a doubt.

I recommend that you read: How to lie with Statistics by Darrell Huff.