Slashdot Mirror
1 In 4 Statisticians Say They Were Asked To Commit Scientific Fraud (acsh.org)
As the saying goes, "There are three kinds of lies: lies, damned lies, and statistics." We know that's true because statisticians themselves just said so. From a report: A stunning report published in the Annals of Internal Medicine concludes that researchers often ask statisticians to make "inappropriate requests." And by "inappropriate," the authors aren't referring to accidental requests for incorrect statistical analyses; instead, they're referring to requests for unscrupulous data manipulation or even fraud. The authors surveyed 522 consulting biostatisticians and received sufficient responses from 390. Then, they constructed a table that ranks requests by level of inappropriateness. For instance, at the very top is "falsify the statistical significance to support a desired result," which is outright fraud. At the bottom is "do not show plot because it did not show as strong an effect as you had hoped," which is only slightly naughty.
As long as there is the incentive to get the results the sponsor wants, there will be fraud.
1 in 4 biostatisticians...
Dollars to donuts it's much worse in the soft 'sciences'. Slightly remediated by the fact they're too stupid to realize what they were asking was wrong.
John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
1 out of 4 are asked to commit fraud.
2 our of 4 are "expected" to commit fraud without being asked.
1 out of 4 are actually trying to get at some form of truth.
Statistics are always biased by their sample sizes, and criteria.
There are lies, damn lies, and then there are statistics.
But if an experiment is only performed once, never scrutinised, never checked, never tested then there can be little or no confidence in its conclusions.
politicians are like babies' nappies: they should both be changed regularly and for the same reasons
"How to Lie with Statistics" lol
;)
Just my 2 cents
My own experience as a statistician is that at least seven in four of us have produced dubious numbers.
Statistics about statistical fraud. Down the rabbit hole we go.
Starships were meant to fly, Hands up and touch the sky - Nicky Minaj
Lying is a life skill.
Part of that skill is knowing when. Peer reviewed papers is a dumb place to lie.
You live in clearlake dumbass.
John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
Drinkypoo is just too much fun to counter troll.
John McAfee 'It was like that time I hired that Bangkok prostitute; to do my taxes, while I fucked my accountant'
During WW2, many people allowed Jewish refugees to hide in their homes. When Nazi guards came around and asked if there were any Jews in the building, these people directly and flatly lied to them. And it wasn't a white lie. Yet it was the morally right thing to do.
So your statement about white lies being the only acceptable form of lie is false. Furthermore, there are times when white lies are more harmful, because someone needs to know the truth even if it will hurt their feelings.
Lying is a complex thing. Most of the time, it is morally wrong. But it is hard to craft a simple formulation for when it is morally right.
That's 25% for all you math majors out there.
3 out of 4 didn't have to be asked.
Were they offered bribes?
They only show what the author wants you to see, period. Whether biostats guy wants to lie to us or not... if his data bogus then stats are bogus.
No stats are even likely valid without *FULL* data being presented with nothing hidden or omitted. It is filtering process or dropping outliers, makes the stats falsehoods at best.
Remember with stats... any data can *prove* anything by at least misdirection.
A liar (scientist or not) can make a lie sound like the truth. Science does occasionally have bad actors who lie. Their lies are discovered and corrected sooner or later.
What was your point again?
This is same as the proof that shows 1=2.
A=B
A*A=B*A
A*A-B*B=B*A-B*B
(A+B)(A-B)=B(A-B)
A+B=B
B+B=B
2=1
"The same?" Well, no. Anyone who has take high-school math (and that includes scientists) can spot the flaw in your "proof." When you divided out the (A-B) factor, you divided by zero.
Or the hotel $1
3 guys check into a room
Room cost $30 (long ago)
Each paid $10.
Night Audit determined the over charged, should be $25 (honest place)
Bellman sent up with $5 to return to them (yes still have them too)
Guys did not have change to split... so each took $1
They gave the bellman $2
So, Each paid $9 for the room for $27
and paid $2 to bellman, for a total of $29
Where is the missing dollar?
There is no missing dollar. The hotel ended up charging the 3 guys $25. They paid $27. The bellman collected a $2 arbitrage ($27 - $25 = $2.)
If it weren't for deadlines, nothing would be late.
The only good lies are the ones that promote what I want to believe. Also known as âoethe greater goodâ.
I think you underestimate just how much I just dont care.
Anyway better in IT than in stats
Ceci n'est pas une Signature !
>> 1 In 4 Statisticians Say They Were Asked To Commit Scientific Fraud
One chance in 4 that this statistic is rigged. Who did the statistics about corrupting the statisticians ?
aaaaaaa
This reminds me of a story an acquaintance of mine once told me. She has a Ph.D. in statistics and has put in a couple of decades with a major biotech firm. A friend of hers was doing a Ph.D. in engineering and had some data to analyze, but he wanted to make sure his conclusions were statistically sound. He asked her to check his work and let him know if he had made any big errors. I'm sure nobody will be shocked to learn that he made some basic errors that non-statisticians make all the time (I think it had something to do with multiple comparisons). Once the analysis was done properly, none of his data showed the level of statistical significance he was chasing.
But did that stop him? No way! He went back and collected more data -- oh wait, no he didn't. He threw out the correct analysis and kept his original (incorrect) work for publication. And my acquaintance no longer does free statistical analysis as a favor to anybody because she thinks she'd be wasting her time.
Where we not only rely heavily on statistics and proxies (because real data is hard to get), we rely on models of statistics and proxies. No wonder the results are all over the map. Being skeptical is not only a good idea in this case, it really is demanded by the process.
"We receive as friendly that which agrees with, we resist with dislike that which opposes us" - Faraday
The authors surveyed 522 consulting biostatisticians and received sufficient responses from 390
My guess is the ones that didn't respond are guilty of doing it putting the number a lot higher than they claim.
I didn't know Spray Tan was a medical problem. Somebody should probably tell the cast of Jersey Shore.
Did they specify the percent who requested they lie were women researchers,
or raised under single mother,
or #NoFaultDivorce'd muted fathers?
What percent of Statisticians agreed to (so perhaps lied) & the percentage of them women, ...
or raised by single mother,
or
1/3 of mothers #ParentalFraud (stat. sample of All women) to those they 'love'.
Most would sell your&Children's soul to damnation just for the pleasure of watching them Suffer/suicide/die.
No Vote, no legal contracts, no testimony, no place of power over others,..
#SexSegregation
https://medium.com/@jimpreston...
This sample shows 30%, near 1/3 of children&men are victimized by Parental Fraud.
Motherhood is sampling of all women's morals.
1/3 women will actively live life-destroying (to 'loved' husbands/lovers & their children) lies,the rest lie to cover for them.
https://twitter.com/StevWork
Can we truly trust this statistic...? I mean look who came up with it.
-Myke