>> found that 62% of respondents reported no or limited statistical knowledge
The other 38% didn't understand the question...(my extrapolation)
I did a couple semesters of statistics at uni. And I can confidently say that the number of people who can answer 3 simple questions on statistics (like say mean versus medians, confidence levels or margins of error) is, well, a rounding error from 0.
Indeed, statistically, no-one has a clue how statistics work.
I did however learn enough to know that statistics can tell you absolutely anything you want them to say. Assuming you don't just make them up, they're trivial to manipulate to generate the headline you want.
When used to evaluate risk, the comprehension goes down further (a fact willfully exploited by any decent marketing.)
> mean versus medians, confidence levels or margins of error
It's basic when you are attending an undergraduate course but most people can understand mean (as a dictionary might generically define it) and have a general feeling for margin of error (again, not in the mathematical way.)
Statistics has been the most difficult course in my CS course. For some reason when I start counting events to get a probability I find several perfectly plausible ways to count them, get five different probabilities and none of them is the correct answer.
And about being "trivial to manipulate [numbers] to generate the headline you want" a politician once told me that you can show the same numbers in any way you want, as in to demonstrate a thesis or its opposite.
One of my favourite jokes: 93 % of statistics are made up on the spot, and 61 % of people believe them.
Bonus points for changing the figures every time you retell the joke.
You _have_ to change the numbers each time, because you're constantly measuring and these things have basic variation. It would be unrealistic if the fake statistics were the same every time!
I started thinking about this percentage on decision makers around the world and got a chuckle.
I've been trying to talk about the median vs. mean with a bunch of politicians on themes around the zillionaires, wealth or consumption and for most parts they're clueless. Or the ones with degrees still go with the normal (mean that skews the normal) as they're afraid.
I just happened to get a copy of naked statistics yesterday, as I feel the human traits of poor comprehension of probabilities can be enhanced to at least some extent. And my degree from the social side didn't include statistics.
If there are better entry-level books on the matter I'm happy to take some recommendations.
Exactly. 38% is way too high. Are we sure about that? Statistics is not some required learning in school. Even those who learned (me for example) cannot confidently claim what it actually means. I would say most of the people don't have a clue what statistics mean
i mean, the headline statistic can be misleading, but you gotta dig in and wrestle with the details. just like anything, we cannot boil down complex things to single numbers and expect any sort of meaningful signal. we gotta roll up our sleeves, look at definitions, think about what our actual questions are, how we might answer those questions through measurements and observations, and what the confounders are. i think a common issue folks have with stats is that they expect a tidy answer, and it just doesn't do that: it's more of a way to prove the world...the results still need some interpretation.
Even leaving aside the quantitative stuff (p-values, medians, whatever) and can't crunch the math, IMHO at least you should have seen how statistics can lead you to the exact opposite conclusion from reality, so that you at least know whether to think twice about a conclusion drawn from statistics thrown at you. Yet I was recently quite surprised to learn that even many folks in tech had never encountered Simpson's paradox before. All it takes to start explaining that is a scatterplot and a few lines, and yet it doesn't seem to be taught widely. It's rather terrifying, given that most people (myself often included) will be happy to believe "obvious" conclusions drawn from seeing one percentage greatly exceed another.
The fact that 62% of Americans have little or no understanding of statistics may be related to those 40% of Americans that believe in Creationism, i.e. human (and fossils) were created by God a few thousands of years ago, and not of randomness and evolution over millions of years. I think no other industrial country has that disbelief in science.
https://news.gallup.com/poll/261680/americans-believe-creati...
This problem with science is apparent in another survey: in 2009, a Pew Center publication showed that 33% of scientists in the USA believed in God (and 18% in a transient power), which is much lower than the 80% belief of the general American population at the time. Of course, this is not a proof of causality in either direction, but scientific knowledge is seemingly inversely correlated to religiosity. And the USA are still more religious than any other industrial more-or-less-democratic country.
A coarse understanding like "the smaller p-value is the more likely a headline is true" is worse than no understanding at all. I bet most people who believed they understood what p-value is are like that though.
I'd say in reality it's way more than that. The first statistics course in uni was a very humbling experience. I realised that while I thought I understood a lot (and I was coming from a CS heavy background, olympiads and such) real statistics is way harder and a lot more counterintuitive than I thought. Granted, this talks about "basic" statistical understanding, but even that is way more complicated than most people assume.
This was abundantly clear when people, even on HN, were upset about the bureau of labor statistics revising their numbers tendentially downwards, probably confusing the notion of statistical bias for that of political bias.
If the figures are biased, just estimate the bias and correct for that, what is the big deal they said, as if the bias variance tradeoff was not a thing.
> The survey showed that 62% of U.S. adults self-report having little to no idea what statistics or statistical concepts like p-values are, but 90% of them would base decisions on reported statistics at least sometimes if they understood them better.
You're kidding, right? 38% self-report more than that? If their self-report were accurate it would imply an education system that has truly excelled.
> How much do you understand about statistics and p-values?
I suspect that it’s far far less than 38% of people who actually understand statistics to this level. I suspect if someone on HN went around and asked their co workers to explain what a P value is in 2 sentences, it would be less than 10% of a (presumably) highly educated workforce.
I suspect about 40% of adults are unable to tell the difference between mean/median/ mode, or could answer the Monty hall problem, or even “if I flip a coin 3 times are the chances I get heads 3 times in a row”
I mean, the Monty Hall problem is a literal gotcha that trips up literal professors, that's a horrendous example to use as the baseline for "basic understanding of statistics".
Other than that choice of example, I do agree in that I doubt anywhere near 40% of adults have basic statistical literacy. I've played in card game tournaments semi-professionally and just gambler's fallacy + results-oriented thinking alone make it so easy to take other people's money, and if you can't figure out such basic concepts as "getting tails once doesn't mean I'm due for a heads next flip" even when you're literally losing money, what are the chances of anyone else caring about understanding it when they're not even being given the hands-on reward-based reinforcement learning opportunity?
Back in the 70's I used to walk 20 miles as a child, and then go for farm work (not eveyday). As a mining engineer, I used to walk up 1.5 miles along a 1:3 incline (tunnel) everyday, sometimes during midnight, working 6-day week. Worked in dirtiest, noisy coal mines, near blast sites, soaked in black dust, with no place to sit during the shift. But never felt that it's something hard or bad, until some college kids, for who I was a tour guide, told me in horror that they wouldn't ever venture working in such place.
My boss laughs at that. He receives anonymous red-letter notes from the local extremist organization threatening him. He keeps a pile of those notes on a spike.
Nope. It's a true story. And how it relates to thread is given below in another of my comments. "Things change with time" should have given you some relation. Statistics is seen by the current generation as hard work, rightly so, due to availability of easier ways of dealing with it.
Statistical literacy, or any literacy for that matter, requires hard work that is seen as a normal way of life. When machines do that hard work for us, it is no longer seen as a normal thing, but some unnecessary hard work (when we have cars, why walk 20 miles? And we have machines that do statistics).
Just like how those college kids saw my work as horrifically weird hard work, while I saw it as a normal thing.
My interpretation is how the risks (statistics) of those job functions are more known, people choose to avoid them. But the people that are-the-statistic don't necessarily agree with or understand those statistics.
For example, if OP is a coal miner that hasn't had health issues yet, they may choose to discount statistics that declare x% of coal miners have negative health outcomes.
Oh we used to dream of only walking 20 miles a day.
We used to get up at 3am half an hour before we went to bed, eat a lump of cold poison then walk FOURTY miles uphill to school then when we got home our Dad would slice us in two with a bread knife
What does it really mean to properly understand p-value? What I remember is that if the p-value is less than 0.05, the research result is considered statistically significant. That's about as far as my memory goes. I know that's actually a misunderstanding, but that's how most people understand it. I'm not sure how much I need to know to say I truly understand it.
Agree. I think it's more important to understand statistical fallacies (selection bias, regression to the mean, survivorship bias, etc). Those are extremely common trip wires but to recognize them you don't need to memorize formal definitions.
Fair play to you for answering, but that’s not what a P value is! A p value is the chance of getting a result greater than the result you actually got, _assuming you are testing a hypothesis_.
I’m also pretty sure I would fall in the camp of saying “nope don’t understand P values” as I can’t remember anything else about them.
Same. I think it involves doing some other stuff very much properly... Like formulating whole thing... And even then you might luck out if you try enough of things...
So I admit I only know that P values are somewhat useful some of the time.
I think the average person is definitely intelligent. It's just that we are very prone to mixing intelligence with knowledge in addition to also forgetting how long it took us to learn things that are so automatic for us we see them as trivial.
Given that most measures of intelligence follow nearly normal distributions (as long as you stay away from the tails), I think it doesn’t matter that much.
>> found that 62% of respondents reported no or limited statistical knowledge
The other 38% didn't understand the question...(my extrapolation)
I did a couple semesters of statistics at uni. And I can confidently say that the number of people who can answer 3 simple questions on statistics (like say mean versus medians, confidence levels or margins of error) is, well, a rounding error from 0.
Indeed, statistically, no-one has a clue how statistics work.
I did however learn enough to know that statistics can tell you absolutely anything you want them to say. Assuming you don't just make them up, they're trivial to manipulate to generate the headline you want.
When used to evaluate risk, the comprehension goes down further (a fact willfully exploited by any decent marketing.)
Statistically, most statistics are meaningless.
> mean versus medians, confidence levels or margins of error
It's basic when you are attending an undergraduate course but most people can understand mean (as a dictionary might generically define it) and have a general feeling for margin of error (again, not in the mathematical way.)
Statistics has been the most difficult course in my CS course. For some reason when I start counting events to get a probability I find several perfectly plausible ways to count them, get five different probabilities and none of them is the correct answer.
And about being "trivial to manipulate [numbers] to generate the headline you want" a politician once told me that you can show the same numbers in any way you want, as in to demonstrate a thesis or its opposite.
> Assuming you don't just make them up, they're trivial to manipulate to generate the headline you want.
well encapsulated in the quote popularized by Mark Twain "Lies, damned lies, and statistics" [1]
[1] https://en.wikipedia.org/wiki/Lies,_damned_lies,_and_statist...
One of my favourite jokes: 93 % of statistics are made up on the spot, and 61 % of people believe them. Bonus points for changing the figures every time you retell the joke.
[delayed]
You _have_ to change the numbers each time, because you're constantly measuring and these things have basic variation. It would be unrealistic if the fake statistics were the same every time!
If you're not yet familiar with it, I present to you the Datasaurus Dozen: https://www.research.autodesk.com/publications/same-stats-di...
I started thinking about this percentage on decision makers around the world and got a chuckle.
I've been trying to talk about the median vs. mean with a bunch of politicians on themes around the zillionaires, wealth or consumption and for most parts they're clueless. Or the ones with degrees still go with the normal (mean that skews the normal) as they're afraid.
I just happened to get a copy of naked statistics yesterday, as I feel the human traits of poor comprehension of probabilities can be enhanced to at least some extent. And my degree from the social side didn't include statistics.
If there are better entry-level books on the matter I'm happy to take some recommendations.
> I did however learn enough to know that statistics can tell you absolutely anything you want them to say.
When told to a statistically illiterate person who isn't aware of Simpson's paradox and so on?
> When told to a statistically illiterate person?
Which is a rounding error from 100% according to the GP.
You mean, the other 48% didn't understand the question. :)
>> found that 62% of respondents reported no or limited statistical knowledge
Combined with Dunning-Kruger, this means that the real number of people completely clueless about statistics is closer to 38%.
Exactly. 38% is way too high. Are we sure about that? Statistics is not some required learning in school. Even those who learned (me for example) cannot confidently claim what it actually means. I would say most of the people don't have a clue what statistics mean
If you changed "most" to "all" you'd be well inside the margin or error.
There's a reason actuaries get paid the big bucks.
One can get paid the big bucks without a clue what they do, even some of the most brilliant statisticians do acknowledge the ambiguity of stats.
i mean, the headline statistic can be misleading, but you gotta dig in and wrestle with the details. just like anything, we cannot boil down complex things to single numbers and expect any sort of meaningful signal. we gotta roll up our sleeves, look at definitions, think about what our actual questions are, how we might answer those questions through measurements and observations, and what the confounders are. i think a common issue folks have with stats is that they expect a tidy answer, and it just doesn't do that: it's more of a way to prove the world...the results still need some interpretation.
Even leaving aside the quantitative stuff (p-values, medians, whatever) and can't crunch the math, IMHO at least you should have seen how statistics can lead you to the exact opposite conclusion from reality, so that you at least know whether to think twice about a conclusion drawn from statistics thrown at you. Yet I was recently quite surprised to learn that even many folks in tech had never encountered Simpson's paradox before. All it takes to start explaining that is a scatterplot and a few lines, and yet it doesn't seem to be taught widely. It's rather terrifying, given that most people (myself often included) will be happy to believe "obvious" conclusions drawn from seeing one percentage greatly exceed another.
The fact that 62% of Americans have little or no understanding of statistics may be related to those 40% of Americans that believe in Creationism, i.e. human (and fossils) were created by God a few thousands of years ago, and not of randomness and evolution over millions of years. I think no other industrial country has that disbelief in science. https://news.gallup.com/poll/261680/americans-believe-creati...
This problem with science is apparent in another survey: in 2009, a Pew Center publication showed that 33% of scientists in the USA believed in God (and 18% in a transient power), which is much lower than the 80% belief of the general American population at the time. Of course, this is not a proof of causality in either direction, but scientific knowledge is seemingly inversely correlated to religiosity. And the USA are still more religious than any other industrial more-or-less-democratic country.
A coarse understanding like "the smaller p-value is the more likely a headline is true" is worse than no understanding at all. I bet most people who believed they understood what p-value is are like that though.
I love how they include statistics in the headline of a story about the lack of understanding of statistics. Epic troll.
100% of headlines of statistics-related articles must follow this rule.
I'd say in reality it's way more than that. The first statistics course in uni was a very humbling experience. I realised that while I thought I understood a lot (and I was coming from a CS heavy background, olympiads and such) real statistics is way harder and a lot more counterintuitive than I thought. Granted, this talks about "basic" statistical understanding, but even that is way more complicated than most people assume.
This was abundantly clear when people, even on HN, were upset about the bureau of labor statistics revising their numbers tendentially downwards, probably confusing the notion of statistical bias for that of political bias.
If the figures are biased, just estimate the bias and correct for that, what is the big deal they said, as if the bias variance tradeoff was not a thing.
Well, that's what happens when you use words like math and not maths. Although us Brits aren't that much better.
That’s surprisingly self-aware, and encouraging.
That's like ⅐ of the US population..
“More than half” may mean anything between 50 and 100 percent. :)
But if they release headline “62% of respondents” reported no or limited statistical knowledge while only 11% regularly use statistics in daily life…
…then they would loose more than half of readers who don’t know “per cent” or % symbol (?)
I thought that OP changed the original headline but no, psu.edu really published this :)
It could be 1/14th. That's twice as many.
> The survey showed that 62% of U.S. adults self-report having little to no idea what statistics or statistical concepts like p-values are, but 90% of them would base decisions on reported statistics at least sometimes if they understood them better.
You're kidding, right? 38% self-report more than that? If their self-report were accurate it would imply an education system that has truly excelled.
> How much do you understand about statistics and p-values?
I suspect that it’s far far less than 38% of people who actually understand statistics to this level. I suspect if someone on HN went around and asked their co workers to explain what a P value is in 2 sentences, it would be less than 10% of a (presumably) highly educated workforce.
I suspect about 40% of adults are unable to tell the difference between mean/median/ mode, or could answer the Monty hall problem, or even “if I flip a coin 3 times are the chances I get heads 3 times in a row”
I mean, the Monty Hall problem is a literal gotcha that trips up literal professors, that's a horrendous example to use as the baseline for "basic understanding of statistics".
Other than that choice of example, I do agree in that I doubt anywhere near 40% of adults have basic statistical literacy. I've played in card game tournaments semi-professionally and just gambler's fallacy + results-oriented thinking alone make it so easy to take other people's money, and if you can't figure out such basic concepts as "getting tails once doesn't mean I'm due for a heads next flip" even when you're literally losing money, what are the chances of anyone else caring about understanding it when they're not even being given the hands-on reward-based reinforcement learning opportunity?
Things change with time.
Back in the 70's I used to walk 20 miles as a child, and then go for farm work (not eveyday). As a mining engineer, I used to walk up 1.5 miles along a 1:3 incline (tunnel) everyday, sometimes during midnight, working 6-day week. Worked in dirtiest, noisy coal mines, near blast sites, soaked in black dust, with no place to sit during the shift. But never felt that it's something hard or bad, until some college kids, for who I was a tour guide, told me in horror that they wouldn't ever venture working in such place.
My boss laughs at that. He receives anonymous red-letter notes from the local extremist organization threatening him. He keeps a pile of those notes on a spike.
Are you a bot? Are you sure that you are answering in the thread that you meant to?
Nope. It's a true story. And how it relates to thread is given below in another of my comments. "Things change with time" should have given you some relation. Statistics is seen by the current generation as hard work, rightly so, due to availability of easier ways of dealing with it.
Wait... Your second paragraph is jarringly different from the first. How do they relate?
And how do either of them relate to statistical literacy in the United States?
Statistical literacy, or any literacy for that matter, requires hard work that is seen as a normal way of life. When machines do that hard work for us, it is no longer seen as a normal thing, but some unnecessary hard work (when we have cars, why walk 20 miles? And we have machines that do statistics).
Just like how those college kids saw my work as horrifically weird hard work, while I saw it as a normal thing.
My interpretation is how the risks (statistics) of those job functions are more known, people choose to avoid them. But the people that are-the-statistic don't necessarily agree with or understand those statistics.
For example, if OP is a coal miner that hasn't had health issues yet, they may choose to discount statistics that declare x% of coal miners have negative health outcomes.
This feels correct. It's why they included the tidbit about their youth, they're saying their job was better than the life they grew with.
I think they are saying as information (statistics) are known about the risks of those jobs, less people are interested in performing those jobs.
Oh we used to dream of only walking 20 miles a day.
We used to get up at 3am half an hour before we went to bed, eat a lump of cold poison then walk FOURTY miles uphill to school then when we got home our Dad would slice us in two with a bread knife
Luxury!
> How much do you understand about statistics and p-values?
Is that a well designed survey question?
I would expect the use of a specific jargon term in that question to affect the results in a significant way.
The question asked as part of the survey: “how well do you understand p-values?” Most scientists may not even be able to pass truthfully.
https://en.wikipedia.org/wiki/Misuse_of_p-values
What does it really mean to properly understand p-value? What I remember is that if the p-value is less than 0.05, the research result is considered statistically significant. That's about as far as my memory goes. I know that's actually a misunderstanding, but that's how most people understand it. I'm not sure how much I need to know to say I truly understand it.
Agree. I think it's more important to understand statistical fallacies (selection bias, regression to the mean, survivorship bias, etc). Those are extremely common trip wires but to recognize them you don't need to memorize formal definitions.
Fair play to you for answering, but that’s not what a P value is! A p value is the chance of getting a result greater than the result you actually got, _assuming you are testing a hypothesis_.
I’m also pretty sure I would fall in the camp of saying “nope don’t understand P values” as I can’t remember anything else about them.
Same. I think it involves doing some other stuff very much properly... Like formulating whole thing... And even then you might luck out if you try enough of things...
So I admit I only know that P values are somewhat useful some of the time.
> The bigger half of adults in the U.S. admit to lacking basic statistical understanding
FTFY
wow, more than half..
"Think of how stupid the average person is, and realize half of them are stupider than that." — George Carlin
I think the average person is definitely intelligent. It's just that we are very prone to mixing intelligence with knowledge in addition to also forgetting how long it took us to learn things that are so automatic for us we see them as trivial.
Shouldn't that be the median person for the quote to actually hold?
Given that most measures of intelligence follow nearly normal distributions (as long as you stay away from the tails), I think it doesn’t matter that much.
and who considers themselves to be in that lower half? Probably a lot less than half of the population
99.99% actually.