Averages. They’re almost always a bullshit flag if it’s tied to anything remotely political. If you’re not going to also give the standard deviation and skew then at least use median.
Probably to support racism. Like the black people crime statistics.
Yeah. Eugenics. It’s convinced a lot of smart people.
To cherry pick it and use it to promote fascist views
…as a drunken man uses lamp posts — for support rather than illumination.
The question makes me remember Daryl Bem, a celebrated social psychologist. He published a much cited article called “Writing the Empirical Journal Article”. About 15 years ago, he used this advice to prove that humans can see into the future. His advice is probably still used to teach. That’s probably the worst thing you can do.
By using unrelated data to prove a point.
Or misrepresenting data.
For example, if your country has a 10% crime rate. Meaning 10% of the population will commit a crime at some point. Due to worker immigration the country gains 20% more people. The it is expected that of those workers about 10% will commit a crime. Thus increasing the total amount of crimes committed in the country but the crime rate is still at 10%.
Now misrepresenting would be to cry out that the workers are bad because the amount of crime has gone up.
96.3 % of all statistics are misleading.
87.7% of statistics are made up on the spot.
99.7% of general questions about statistics have this same joke at least once in the replies
100% I’m gay
Bonus points for three standard deviations
correlation and causation. even useless stats comparing apples and oranges, the numbers generated are only as good as the study design and methods.
Blindly. People love to list them as evidence as if the numbers stand on their own. Reality is a person had some hand in assembling the numbers and there is no such thing as a bulletproof statistic. Good statistics ought to be scrutinized.
As a math guy, I hate when people say statistics is math. Like yeah, there are equations, and math plays a role, but the results so often speak more to the selection and interpretation choices made by the statistician than to any kind of mathematical rigor.
By training an algorithm that will have an impact on said statistics. Not only the algorithm can cheat (see Goodhart’s law), but it can repeat biases that led to these statistics (like those law enforcement algorithms that became racists)
My favorite was the one they were training to detect cancer in imaging scans but they forgot to edit out the info stamp in the corner so it just started flagging all the scans from the cancer center!
Oh, I hadn’t heard of that one. That’s quite funny
A similar case was with scans from “mobile scanners”. Since those are used on patients to sick to be transported, their cases were disproportionaly “malicious”. Model was effectively optimozed to detected if scaner was stationary or mobile.
You are describing Google Ads right now. Algorithms are better and better in reaching to poeple that are already on the purchase patch. It’s like giving a restaurant flayers to people that are waiting for a weiter to show them a table.
Aren’t our ads amazing? Look, almost everyone who saw them made the purchase!
Analytics that ignores Goodharts law ruin everything. Movies, HR, Marketing (not much to ruin left, but you get the point), performancet review, recommendations…
Well, to immanetize the eschaton. That’s the worst thing to do with statistics.
When you mix statistics with marketing.
Not making sure the result even makes sense. There was a real example, where a ~2010 news article said that the number of crimes in their city has been doubling every year since ~1980.
That is not possible. Assume that there was one crime in 1980. In 2010, there must be at least 2^20 crimes.
I once saw a reddit post where some busybody counted how many people with dogs walked by in an hour and multiplied that by 24 and assumed that was how many walked by in a day (as if it would be the same amount at all times of day)
“Facts are stubborn things, but statistics are pliable.” ― Mark Twain
On people who dont understand them to paint an incomplete picture of reality. Misleadingly.
