What would be some fact that, while true, could be told in a context or way that is misinfomating or make the other person draw incorrect conclusions?
The introduction of seatbelt legislation lead to an increase in nonfatal vehicular injuries
Similarly, the introduction of metal helmets for soldiers corresponded with an increase of head injuries.
Body armor in the second Gulf war contributed greatly to an increased rate of amputations on soldiers.
Ah, survivor bias. Reminds me of analysis of damage to bombers in WW2. Data showed most damage was done to the wings and body of planes. The tail, cockpit and engines were rarely damaged. They responded by reinforcing those areas that were frequently damaged.
However they were only observing bombers that made it back to base and so data on planes that were shot down was missing. Luckily someone did eventually realise this and so the research could be used as evidence that strikes to the areas rarely recorded indicated a downed plane.
When metal helmets were introduced in the middle of WW1, head injuries went up!
those damn seatbelts!
test
Test back
Light roasted coffee has more caffeine than dark roasted coffee.
Technically, per bean, more of the caffeine is cooked out of the dark roast. However, other things are also roasted out of a dark roast to the point that the individual beans are also lighter and smaller. When brewing coffee, usually you either weigh your dose of beans out, or you use a scoop for some consistency. Either method will result in more dark roast beans ultimately making it into the brew than would with a (larger, heavier) light roast.
Typically, this more than cancels out the reduced caffeine content per bean, so a brew of dark roast coffee still typically has more caffeine in it.
If I remember correctly, dark roast was also originally devised to hide bad-quality coffee beans. Nowadays it is often implied that darker roasts are better, which actually isn’t necessarily the case.
Implied where? All the coffee snobs ik ow drink lighter roasts and derogatorily call dark roasts “supermarket coffee”
Can confirm. Source: am coffee snob.
Dark roasts have a more consistent taste/flavor and it has a longer shelf life, so it’s easier to know what you’re getting. If you want to taste the variety of flavors coffee can have, you’ll go for fresher lighter roasts.
Yup, I had to explain this to so many people when I sold coffee. Nobody believed me at all. I explained that dark roast had more of the caffeine cooked out of it.
Oh shit I’ve repeated this to people and confidently claimed I can “feel” the difference with light roasts. Brains are stupid.
“Brain make people dumb” – says the brain. How can I trust it?
/Everything/, says the brain.
Can’t trust what the brain says, it makes people dumb.
This is actually very interesting and I had no idea. Thanks!
This is actually very interesting and I had no idea. Thanks!
This is actually very interesting and I had no idea. Thanks!
This is actually very interesting and I had no idea. Thanks!
This is actually very interesting and I had no idea. Thanks!
Thank you for laying it out like this. I’d often heard that about light roasts, but had never noticed any difference in my caffeine response when I switch roasts. At any rate I’ve always preferred dark for the flavor, but it’s good to know I’m not sacrificing any buzz for it!
James Hoffman did a great video on this, and yes, kinda. It’s complicated.
This is actually very interesting and I had no idea. Thanks!
I’ve honestly never thought of that. Guess that’s why I’ve not been able to feel a real difference in my morning coffee when I use different roasts. I always thought “well it can’t be losing that much caffeine because it doesn’t feel any different than my medium or light roasts.”
new comment
As ice cream sales in the United States increase, so do deaths in in developed parts of Africa.
I use this fact to explain to students how true information can be used to mislead people into drawing wild, deranged conclusions.
The commonality in these events is the rise in temperature during the summer. But if you leave that out, there’s an absurd argument to be made about how purchasing ice cream is inherently evil.
I don’t think it’s an amazing example of what OP is talking about, but as an example, I like how simple and easy to follow it is. Great for junior high level kids.
According to a new study published by the University of Berchul, eating ice cream can make you be in risk of drowning.
Is this related to correlation is not causation?
Correlation at least tries to imply they’re related. As lottery sales go up in your household so does credit card debt. Not always a cause but they’re related
You’re looking for spurious correlations which is when numbers have no business even being used in a comparison
I mean, they are related. There’s a common causation (higher temperatures). There’s plenty of spurious correlations but this specific example isn’t it
yes
Not exactly. What you’re looking for is coincidence.
But correlation is sometimes caused by coincidence.
Do you have an example? I’m pretty sure correlation cannot be caused by coincidence.
Coincidence is describing two things happening at the same time but with separate causes. Correlation is describing two things having a common cause.
Here you go: https://www.tylervigen.com/spurious-correlations
First thing you learn in a statistics course is that correlation doesn’t equal causation.
Correlation: two thing happening at the same time or one thing happening right after the other, regardless of whether the things are at all connected
Causation: one thing happening BECAUSE of the other
Oh yes I got my definition of correlation slightly wrong. Correlation doesn’t necessarily mean that two things have the same cause but they do relate in some way either by having a common cause or by occuring in the same system. They definitely have more in common than happening just at the same time or right after each other like a coincidence.I didn’t claim that correlation equals causation and I hope you didn’t get the impression because this would be oviously wrong.Edit: I stand corrected and today I learned that “correlation” means that two things have a statistical relation without any causal relation implied. There can be a causal relation but it’s not necessary. The key takeaway for me is that correlation describes a statistical relationship.
So there’s some “incorrect” assumptions you have made about the North American summer, and weather in Africa. In the North American summer, only North Africa experiences summer with you guys. The rest of the continent is blanketed in rains (West, Central and East Africa) or are in outright winter (Southern Africa). So our temperatures do come down in your winter. Your coldest months are our hottest months for most of the continent (except for North Africa). So saying the developed parts of Africa
In equally unrelated news, there’s also a direct correlation between ice cream sales and shark attacks. We have to steal all the ice cream before more people get eaten!
Dihydrogen Monoxide, commonly used in laundry detergent and other cleaning supplies, is also present in Subway sandwiches
FACT: 100% of people that consume Dihydrogen Monoxide die.
Wrong, a mortality of 94.5% has been shown not even close to 100%.
One could say that people who haven’t died yet don’t have a cause of death yet so they can’t be counted.
Maybe we can agree on “100% of people who died consumed dihydrogen monoxide beforehand”.
Except for the ones that didn’t.
Please show me the data showing the data on pre-1900s populations proving that 100% of them consumed dihydrogen monoxide. You can’t do it.
They even put it into the water supply.
Evil!!
It can even be found in unborn babies!
Everyone who has died has ingested dihydrogen monoxide.
You are much more likely to die in a hospital than anywhere else.
Wait until you hear the fatality rate for hospice residents
I don’t think this one is true, unless you mean it a different way than I’m interpreting it.
https://www.nejm.org/doi/full/10.1056/nejmc1911892#:~:text=In 2003%2C a total of,%25)%20to%20534%2C714%20(20.8%25).
(This is the US)
deleted by creator
‘true fact’.
- Facts cannot be anything except for true.
- Anyone who uses the two words ‘true fact’ together cannot be trusted because they know neither the meaning of the word ‘true’ or the word ‘fact’.
Oh how I miss the before times.
Counterpoint: True Facts is a great series of humorous nature documentaries.
Imagine trying to move by riding a unicycle backwards and throwing up through a giant straw. That is how the nautilus do.
True facts.
I can’t trust you on this because you are using the words ‘true fact’.
What about “alternative facts”?
Facts are just objective statements, which can be either true or false, but whichever they are it is objective and not dependant on the observer.
I mean, it’s a semantic argument, and semantics is subjective, but that’s probably how the people who say ‘true fact’ are defining fact.
No, a statement can be true or false. A fact is always true.
That’s why I clarified that the definition of any word, including the word fact, is subjective.
No it’s not or we’ll bicker over every word and square could mean triangle. We have agreed upon word definitions. That’s part of a language.
Language is constantly evolving. Deal with it.
That doesn’t mean that word definitions are absolutely not arbitrary nor subjective. They are agreed upon in a civilization at any given time. I don’t have to deal with anything.
this must be one of those false facts
That’s a true fact!
I see your “True Facts” and raise you Kellyanne Conway.
Who called the tautology police?
Natural language is inherently imprecise.
Boom, pedants shook.
I’ve never lost a professional MMA match
The Seattle Mariners have never lost a World Series game
Neither have the Seattle SuperSonics.
Why is it called World Series? You kinda forgot to invite the world.
Wait until you hear about the Miss Universe competition…
(Seriously though, I agree.)
People use to say that you cant lie with statistics, but is a common practice to use statistics to lie.
We can take the infamous 41% suicide rate for trans people. Transphobes throw that out like a killing move implying that trans people are inherently unhappy and being trans is a mental illness (which is not true).
The reality is that the suicide rate is so high because of transphobia, kids getting thrown out of home, homelessness, unable to find a job, staying at the closet to avoid social consecuences, etc.
Trans people who live in more open and accepting environments are way less likely to be depressed and commit suicide. In progresive areas where trans people are more accepted the suicide rate is nowhere near 41%.
Yeah that statistic is brutal. Like I wish more people understood it’s like saying: “we bully the shit out of people who seem depressed, we aggressively stigmatize antidepressant use, X% of people with depression will attempt suicide at some point in their lives. We should ban antidepressants and treat depressed people worse.”
Its so frustrating when I see other minorities use that argument because their suicide statistics are also typically higher! That’s the nature of oppression.
Man, I can’t believe we live at a time where being trans is more dangerous than having cancer…
“Numbers don’t lie” is true in the same sense as “guns don’t kill”…
Numbers don’t lie, but people lie using number all the time.
It depends on how you define “lie” really. A true stat is always true, but a person can draw misleading conclusions from it if they aren’t trained and especially if they also are looking for a certain conclusion.
Hey vis4valentine, you should correct “wish” to “which” in your comment. That typo could cause readers to understand the sentence completely inverted.
I learned that stats is all about lies lol
One of my favorite Brian Regan bits kinda fits, maybe?
“In 1939, Germany invaded Poland. One thing led to another and the United States of America dropped two atomic bombs on the sovereign nation of Japan.”
Clumsy. Did they at least pick them up on the way out?
I love Brian Regan, but I haven’t heard this bit. What’s it from?
it’s from World War II
When you think about data it actually gets really scary really quick. I have a Master’s in Data Analytics.
First, data is “collected.”
-
So, a natural question is “Who are they collecting data from?”
-
Typically it’s a sample of a population - meant to be representative of that population, which is nice and all.
-
But if you dig deeper you have to ask “Who is taking time out of their day to answer questions?” “How are they asked?” “Why haven’t I ever been asked?” “Would I even want to give up my time to respond to a question from a stranger?”
-
So then who is being asked? And perhaps more importantly, who has time to answer?
-
Spoiler alert: typically it’s people who think their opinions are very important. Do you know people like that? Would you trust the things they claim are facts?
-
Do the data collectors know what demographic an answer represents? An important part of data collection is anonymity - knowing certain things about the answerer could skew the data.
-
Are you being represented in the “data”? Would you even know if you were or weren’t?
-
And what happens if respondents lie? Would the data collector have any idea?
And that’s just collecting the data, the first step in the process of collecting data, extracting information, and creating knowledge.
Next is “cleaning” the data.
-
When data is collected it’s messy.
-
There are some data points that are just deleted. For instance, something considered an outlier. And they have an equation for this, and this equation as well as the outliers it identifies should be analyzed constantly. Are they?
-
How is the data being cleaned? How much will it change the answers?
-
Between what systems is the data transferred? Are they state-of-the-art or some legacy system that no one currently alive understands?
-
Do the people analyzing the data know how this works?
So then, after the data is put through many unknown processes, you’re left with a set of data to analyze.
-
How is it being analyzed? Is the analyzer creating the methodology for analysis for every new set of data or are they running it through a system that someone else built eons ago?
-
How often are these models audited? You’d need a group of people that understand the code as well as the data as well as the model as well as the transitional nature of the data.
Then you have outside forces, and this might be scariest of all.
-
The best way to describe this is to tell a story: In the 2016 presidential race, Hillary Clinton and Donald Trump were the top candidates for the Democratic and Republican parties. There was a lot of tension, but basically everyone on the left could not fathom people voting for Trump. (In 2023 this seems outrageous, but it was a real blind spot at the time).
-
All media outlets were predicting a landslide victory for Clinton. But then, as we all know I’m sure, the unbelievable happened: Trump won the electoral college. Why didn’t the data predict that?
-
It turns out one big element was purposeful skewing of the results. There was such a media outrage about Trump that no one wanted to be the source that predicted a Trump victory for fear of being labeled a Trump supporter or Q-Anon fear-monger, so a lot of them just changed the results.
-
Let me say that again, they changed their own findings on purpose for fear of what would happen to them. And because of this lack of reporting real results, a lot of people that probably would’ve voted for Clinton, didn’t go to the polls.
-
And then, if you can believe it, the same thing happened in 2020. Even though Biden ultimately won, the predicted stats were way wrong. Again, according to the data Biden should have been comfortably able to defeat Trump, but it was one of the closest presidential races in history. In fact, many believe, if not for Covid, Trump would have won. And this, at least a little, contributed to the capital riots.
All media outlets were predicting a landslide victory for Clinton. But then, as we all know I’m sure, the unbelievable happened: Trump won the electoral college. Why didn’t the data predict that?
Nate Silver was singing a different tune, though. I remember an interview he gave a month out from the election where he noted significant softness in support for Clinton. There were also a lot of undecideds who might swing elections in key states. That is, of course, exactly what happened. When the Comey letter was leaked by Congress, it likely cost Clinton the election. Her poll numbers dropped from +7% to +3%, well within the advantage that the Electoral College gives to Republicans.
On Election Day, the 538 model was about 3:1 in favor of Clinton. That sounds highly in favor of Clinton, and it is. But it still leaves plenty of room for a Trump win. And lo and behold, she lost.
One other thing polls didn’t really capture was voter enthusiasm or maybe not enough people was paying attention to it. Just because you answered Hilary when asked who would you vote for, it didn’t mean you went out on Election day to vote. A combination of lack of enthusiasm for Hilary, coupled with news constantly reporting that it will be a landslide kept many Democrat voters home.
I believe that’s why there’s such a huge push for “get out the vote” campaigns in 2020 by the Democrats. Generally, the more people voting means better chances for a Democrat win, given general (non-electoral) election results.
That’s interesting, I did not think the letter had that big of an impact.
For me it was Bernie. I remember a lot of us on Reddit were all about Bernie.
Iirc, Bernie had a lot of steam and it seemed like again Clinton was going to be pushed aside for a grass-roots candidate (just like with Barak years earlier).
And Bernie said he was not going to give up the race, because even if he didn’t win the votes he could still be voted in at the national convention.
And as the DNC neared, things were looking great. Clinton was giving paid speeches to wall street and Bernie was tearing her whole campaign apart because he was saying, give money back to people and she was saying keep things the way they were.
And then, among mounting pressure, two weeks before the convention he concieded out of nowhere. At least that’s what it seemed like to us.
Then emails leaked that showed the Democratic Party had colluded with Clinton to get Bernie out of the race!
We couldn’t believe it. We were devestated. So some people went to the DNC and were making a big stir, demanding that Bernie get back on the ballot.
And it all came to a waterfall moment when Sarah Silverman was on stage. And people were chanting Bernie and she lost it and told everybody to shut up and said the Bernie supporters were stupid.
And that was it. The only thing that came out of it was somebody got fired, but there was no regard or representation for us in the Democratic Party anymore.
They didn’t care about what we wanted, and they were just as crooked as they had always told us the Republicans were.
For me it was a massive dissolutionment, and drove me to Trump. Since he was saying we need to take our economy back from the 1%.
I won’t say Bernie supporters weren’t a factor, but the prospect of “buttery males” was an easily measurable factor. Trump was having a really rough few weeks running up to the election. He had a piss poor debate showing, the Access Hollywood tape, and sexual assault allegations all coming together against him. Even with Russia laundering their hack of John Podesta’s emails through Wikileaks and Wikileaks working working with the Trump campaign to drip out the hacks, Trump was well behind. It was hard to see anything with Bernie supporters because that played out over the entire campaign. Meanwhile, the Comey letter had an immediate effect over mere days.
Clinton was giving paid speeches to wall street
Note that Clinton’s speeches were from well before the campaign. When I looked at the transcripts when they got released as part of the Russian hacking, I could see why she didn’t want them released. There were parts where she was being more frank about certain subjects than politicians usually are. It was easy cherry pickings from there. And as much as the paid speech circuit has its detractors, I’d rather see former or dormant politicians giving empty platitudes to rooms full of bankers than lobbying their former colleagues.
she was saying keep things the way they were
At the very beginning of Hillary Clinton’s campaign, she did a tour of the nation and just listened to people’s problems and concerns. From there, she drew up a platform. She has a history of doing this sort of thing like when she was a senator in New York, where she tackled loss of jobs in upstate New York in areas that had been ignored.
She also was pretty blunt with certain areas, like talking in West Virginia about needing to plan for a future after coal. To his credit Bernie didn’t jump in there to attack her, but he also didn’t exactly jump to cover the subject. Trump of course did, lied to the workers, got their votes, and they’re still losing jobs anyway.
And it all came to a waterfall moment when Sarah Silverman was on stage. And people were chanting Bernie and she lost it and told everybody to shut up and said the Bernie supporters were stupid.
She shouldn’t have lost it, but I can see why. I remember Bernie supporters in general getting extremely annoying around that time. It’s the same attitude that we saw out of Trump supporters: everyone I know loudly supports Bernie/Trump, no one I know supports Clinton/Biden, therefore I was cheated. I couldn’t poke my nose up on /r/politics in support of Clinton without getting my face gnawed off.
And that was it. The only thing that came out of it was somebody got fired, but there was no regard or representation for us in the Democratic Party anymore.
There was supposedly a takeover of the DNC by the Clinton campaign. This is a questionable interpretation. tl;dr: A heavily indebted DNC traded fundraising by the Clinton campaign for some control. Nothing stopped Bernie from a similar deal. Also Donna Brazile told the Clinton campaign that there would be two questions: one on capital punishment and the second on lead in drink water. I’m sure she had a stock answer for capital punishment. For the second, the town hall was in Flint, Michigan. Yeah, of course they’re going to ask about lead.
For me it was a massive dissolutionment, and drove me to Trump. Since he was saying we need to take our economy back from the 1%.
Did Trump ever actually say that? I ask the question because Trump does this thing where he leaves himself as a blank canvas. Two supporters with different values can believe contradictory things about Trump without there actually being evidence of a contradiction because he either never said anything or because he just says things without meaning them.
Do you have a source for the outlets changing their poll results? I did a search myself but couldn’t find anything. I find that very interesting and wanted to read more!
It was in an article on Hacker News around that time. It was super interesting, but I can’t find it atm, I’ll look around tomorrow.
Oh yeah. I might say some wrong stuff since I’m quite ignorant but. Statistics is messy and I tend to avoid including too much stats in my projects, although sometimes I accidentally end up blindly doing so and believing them also drawing inaccurate conclusions. Physical stats are even messier because not everybody has the competence to accurately understand what they mean, or sometimes we just don’t understand the world enough. Environmental science data is an example of that. I rely on other people’s analyses cause I can’t read them. I don’t know much about politics.
-
Women have smaller brains than men.
I mean, yes. Women as a population are physically smaller than men as a population.
Women have smaller fingers than men. Smaller eyes. Smaller lungs. There is no “gotcha” that smaller skeletal frames with smaller skulls contain, by volume, a smaller organ.
Doesnt mean every man’s brain is larger than every woman’s brain either.
Doesn’t mean men are smarter than women.
It’s just a statistic, that while true, doesn’t imply what some people think it does.
There’s actually some historical context for this untrue way of thinking.
France, 1873 Paul Broca, a French physician, decides to weigh some brains. And women’s brains weighed less than men’s brains. This is part of his research into crainiometry in which the size of the brain is used to understand a mesure of intelligence. Bigger brain weight = more smart.
We now recognize crainiometry as a pesudoscience.
Then another French academic Gustav Le Bon uses Broca’s research to further engain that not only are women’s brains small causing them to have the big dumb, women are in fact more similar to gorillas in brain size. Thus, women are uncivilized, akin to children, and MUST be under the care and control of men who are CLEARLY more intelligent with their big brains and, naturally, should control and run society.
Broca did not take overall body size or age of the specimens into account when originally weighing the brains. The male specimens were younger and larger to the female specimens who were smaller and older. Brains tend to shrink as we age.
So, not only was this flawed science, based in flawed measurements, thay have been readily disproved, we’re still struggling to undo this as a belief.
History rant over.
Many years ago I worked as an analyst at a small VC firm. My boss, who was a raging misogynist prick and liked to date College freshmen, LOVED this fact (and any other Manosphere bullshit he could find about women being inferior to men). He was such an unbelievable stereotype, he could have stepped out of a sitcom.
Yeah I mean, neanderthals had bigger brains than humans, and they were no smarter than we are (as far as we know.)
Also a blue whale’s brain is four times the size of a human brain and they don’t even know how to drive.
We don’t really know where blue whales go a lot of the time, so I think that’s a bit of an assumption there.
I’m assuming down.
Their hearts are also like four times the size of the human body …but I don’t think they love us very much.
It’s just more impressive that even with a bigger brain he is still a bumbling buffoon.
It’s my pet hypothesis that people are drawn to the comfort of sitcom-level characters because they’re so basic and predictable, even when they’re terrible. Real life is so complicated that black-and-white thinking blasted by people like that is just so low-energy to consume.
Men have bigger balls is another missunderstood fact.
Gonna need a source on that claim
When people say a politician “raised taxes.” More often than not it’s a tax that does not apply to 99.99% of the population and they raised it from 0.000001% to 0.000002%
But boy do those campaign ads look good
Similarly, when a politician says they cut taxes, middle class tax cuts are almost always intend to “sunset”. That is, eventually, those tax cuts are designed to reverse themselves over time.
Maybe in the US. Most tax cuts that happen in Canada at least don’t tend to have an expiry. Although new governments do tend to reverse previous government’s tax policy. Although it tends to apply to tax policy across the board.
And sooooooo many voting Americans hear this and vote Republican.
The average human has less than 2 arms.
And half a penis.
On average, humans have just under 3 inches of penis.
One testicle, and one boob
Average arm has less than one human
Haha, that’s even weirder sounding.
ceiling(AvgArms)
The large percent of traffic accidents that take place within 5 miles of home. Most people only cover a fairly small radius on a day to day basis so it makes sense if there is an accident, it’s close to home and not 80 miles away… just on average of how far how often you drive. Makes it seem like neighbourhoods are more dangerous than highways or something.
Another factor is that people feel more comfortable driving their local roads and get used to usual traffic patterns, which could mean that they’re not as alert if something’s different.
Eg you’re almost home, in your neighborhood, and there’s a stop sign that almost never has anyone else there, so you might not look too much just roll through, the one time someone’s actually there.
The only accident I have ever been in was 1300 kilometers from home…
Well I can’t recall the statistical percentage often cited but I’m sure it wasn’t 100% so it’s ok for it not to have been true for you. Sorry about your far from home accident.
Until today 👀
Alf kinda sus
This is such a good example for how statistics are often misinterpreted without any fault of the statistics itself.
It reminds me of when they looked at fighter jets to decide which parts to reinforce. So they examined which parts had the most bullet holes and came up with this statistic:
If some of you don’t knew about this yet, I let you decide why this effect is called “survivorship bias”. :D
There needs to be more education about how statistics need to be looked at in the correct context.
There are better examples of survivorship bias, but simce this one deals with war and comes with an easy to understand picture, people rarely remember the other examples so only this one ever gets posted.
that is actually an interesting way to think about it
You can see the moon from The Great Wall of China.
But the opposite is not true! At least, not with the naked eye.
The frequency with which I keep hearing this misconception repeated in popular media is boggling. Hell, I feel like I just heard it again recently in the new Star Trek.
