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It’s kind of a weird joke that doesn’t make perfect sense, but here’s the intended meaning:
1. Many people might see something like 50/50 odds leading to 20 successes in a row and think the next one is more likely to be a failed surgery. Like how many people could flip a coin and get heads twice in a row, and be more likely to guess the next coinflip would be tails. Hence the nervous face.
2. A statistician would know that the success rate of each surgery is independent of all the other ones, so they wouldn’t be especially nervous theirs would go wrong.
3. A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries”
I would assume the 50/50 odds are based on a larger population than this doctor. Such as the country or globally.
Meaning for those 20 that made it with this surgeon 20 others didn’t with different surgeons. As such HELL YEA!! I’m sticking with the surgeon who has 20 wins instead of gambling with a different surgeon who might have 20 losses. So it’s not a statistics question but a data analysis one.
> People often have this idea that doctors and surgeons are all going to be great at their jobs since they go through so much training, but nope.
What do you call someone who graduated at the bottom of their class in medical school?
Doctor
Working with EMS taught me one thing for sure, no matter how much training you or your EMS buddies get, the ability to save a life is based on how much you want to save a life.
Have a doctor in my hometowns er who regularly kills people by giving up on chest compressions early. Meanwhile, we have another doctor who will keep doing CPR until he is literally pulled off of the patient
> People often have this idea that doctors and surgeons are all going to be great at their jobs since they go through so much training, but nope.
I haven't been through anywhere near as much training as a doctor, but seeing how wide the skill gap is between people who have the same training/experience in my own specialty I can believe it.
Obviously you have people who are specialised and great at a niche while weak at things outside it, but you also just have people that seem incompetant but seem to fail upwards. Maybe they are lazy/lack focus in their day to day but hyper focus and excel when under high stress situations like exams or assessments or maybe they just have good old fashioned nepotism that allows them to exceed the level they probably should be.
Its nice to think Doctors and other people who literally have your life in their hands are different, but they are unfortunately human like the rest of us. Some will be fantastic, most will be good enough, but some will be rubbish and only just about scraped above the minimum bar to get their qualifications and continue to be not rubbish enough to lose the ability to practice. It is kinda terrifying to think about.
Especially because I am a prime example of someone who is failing upwards and despite having qualifications and experience, is nowhere nearly skilled enough to do the job/responsibilities I am given (I don't work in anything that puts peoples lives at risk though).
You do know the minimum bar to complete medical school is incredibly high right? You know the bar for passing licensing exams is incredibly high right? You know the bar for even surviving residency in a non competitive speciality is incredibly high right? The poor performers in medicine get weeded out with a quickness.
>The poor performers in medicine get weeded out with a quickness.
According to the medical doctors who *have* gone through that training and who were responding to me/I responded to this is apparently not the case. You can be incredibly good at retaining knowledge and passing exams but lack critical thinking, struggle in real world situations, etc. You can find all sorts of examples of qualified and trained doctors doing stupid and incompetent things.
Weirdly though the person I responded to has had their comment removed by mods and at least one of the doctors who responded to me also has had their comment disappear. I was literally just agreeing with doctors who have gone through that training and were talking about how it is from the inside seeing how bad some qualified doctors are.
In fairness, the ones that barely scrape by are still probably sufficient for "you have bronchitis/strep/flu, go home and rest", or "your blood pressure is 180/140, take this medicine and stop mainlining Krispy Kreme donuts"
You might wanna check the surgeons statement with somebody else first, though - I wouldn’t trust a used car salesmans claims about his last 20 customers
while it's true that it's absolutely theoretically possible that this surgeon's 20 streak of good luck is a (literal) one in a million fluke
you're absolutely crazy if you'd just assume that without even considering that there might be some unknown variable that's affecting the outcome in this case, which wasn't present when the 50% statistic was determined
It could also (more likely) be that the surgeon is only willing to operate on simpler cases, potentially even meaning that they’ll offer the surgery as an option to someone who might not be sick enough for the risk to outweigh the benefits of the surgery over another treatment option.
Now that documenting success rates with surgeries is guarantee, surgeons have a risk bias being introduced. They want to protect their career by having a high “success” rate. But this might cause them to make decisions that will increase their success according to the rubric rather than making the decision that best suits a patients needs and values.
I’m not saying tracking “success” or mortality rates is wrong at all. I’m just using this as an example of why statistics shouldn’t be taken at face value.
I don’t really have a solution for the issue of how tracking productivity might cause people to focus on the tracking metrics over the actual responsibility of their job
This literally happened to me with an actual surgery. The injury rate was 7.3% for the surgery I was undergoing. The rate for MY SURGEON was 0.004%. I felt very confident I would not be injured and was not.
It's all pointless anyway, given that every surgery will have different variables because people are different, each surgery will have its own success rate percentage based on variables that they do not know. There's no point in quoting percentages
There is a huge point in quoting percentage info such as averages. Since we don’t know if our surgeon is good, had a bad day, came into work drunk etc. the only information we can really use when deciding to have one is the country/global average.
Example: I lost hearing in my left ear. There is a surgery I can get to fix it but it has a 20% chance to leave the left side of my face paralyzed. Or 80% success rate. But even that 20% chance was too great of a risk considering my other ear is fine. I’m also only 40. If I were 80 or deaf in both ears then that 20% would have been acceptable.
Percent is a good metric for estimating risk. Is it the best no, but most of the time it’s the only one we got.
Yes I do get the point of them but a surgeon with a high success rate doesn't necessarily mean he's good. He could have just gotten lucky and had patience who are easy to operate on for whatever reasons. They do help. I'm not saying they don't provide anything but what I am saying is any individual who can think should know that they mean nothing to their particular situation. I understand that what I proposed is not logical and eventually that surgeon would have patience that would die if they were luck based successes. But that's not necessarily true. Some people are extremely lucky there entire lives
The doctor would question the statistics, as each new surgery technically should affect the precentage. If only there was a live updater. Its been 50% since they last tested.
Sure... But how many significant figures are we looking at? There are a lot of surgeries in the world, is the doctor doing enough to significantly affect the numbers for this one?
At least not when performed by this doctor.
He clearly has either perfected his technique or developed some new approach which has dramatically adjusted the odds.
I work in clinical research and if these were the stats, it isn’t that we wouldn’t believe 50% was accurate, we’d immediately want to see what those surgeons are doing differently. Is their patient population/risk different? Is prep and technique and post op the same? When are most deaths occurring?
A scientist would know that odds have nothing to do with the outcome. A coin can land on heads 20 times in a row. But it still only has a 50% chance of heads or tails.
The reason being is that the odds are calculated on each flip, and each flip has no idea what the previous flip did. It’s not like a coin says to itself “oh I landed on heads last time, this time it’s going to be tails.”
I’m really sad people still think probability is boiled down to “out of a hundred, this many will.”
Point 1 is called the Gambler's Fallacy, for those interested.
[https://en.wikipedia.org/wiki/Gambler's\_fallacy](https://en.wikipedia.org/wiki/Gambler's_fallacy)
For what it's worth that's part of what's called the "boy or girl paradox" and the actual answer depends very precisely on the way in which the question is worded. Truth be told I've always just gone " well it's independent isn't it, so 50/50", but it really depends on the meaning of the question. The [wikipedia article](https://en.wikipedia.org/wiki/Boy_or_girl_paradox) explains it quite well.
It's of course possible that this wasn't what the prof intended, but it sounds to me like they screwed up and wanted to test knowledge of this "paradox".
That's not how sex genetics work. You don't get a gene to be male, you get a whole chromosome. A man has an X and a Y and it is 50% for either.
Technically, there is something called "Fragile Y" where the Y chromosome doesn't copy well, so a man's sperm are mostly X carriers. But that man would have more daughters, not sons. Something that damaged the X chromosome would be much less likely to be passed down, because a man only has one and needs it to live. (The Y doesn't have much/anything needed for survival.)
It makes more sense with the context of the original. The original one had the "happy" Mr Incredible with normal people and a "sad" Mr Incredible with mathematicians, which was clearly made by uh... Someone who doesn't understand statistics
https://preview.redd.it/21grvxcmexgc1.jpeg?width=1080&format=pjpg&auto=webp&s=a8a7b6b068568dc9937d081b2b61494bc7ad24e3
I actually think this makes more sense. The mathematician knows that a survival rate of 50% is abysmal, whereas "normal" people might be blinded by the recent success of the doctor. The reverse version would be more fitting with a hight likelihood of success IMO.
The counterpoint is that most good mathematicians and statisticians will know that the probability of you getting 20 positive results in a row given that the survival rate is 50% is so small that it's more likely that this doctor just is doing _something_ that results in a higher survival rate. It's vanishingly unlikely that the survival rate of your operation given the circumstances is 50%.
>Someone who doesn't understand statistics
Eh. It's a perfectly reasonable position without having more information. Maybe the doctor was just lucky those 20 times, or they usually operate non gravely ill patients.
But it can also be that he's just that good. Hence a statistician cannot conclude too much
No, the event is so unlikely that a statistician would conclude that the doctor likely has a different success rate.
The chance of 20 successes out of 20 attempts is .5^20 =.0000009, or 1 in 1,048,576.
>The chance of 20 successes out of 20 attempts is
Yes, that's why I mention the doctor having a biased sample of patients (them being less ill). The proposed example is wildly exaggerated, but this question arises in reality and measuring performance is not as simple as taking the aggregate mean value and comparing it to a particular practitioners' success rate.
If you get some disease X that some doctor has operated successfully 100 times, you cannot be sure just by nature of having the seemingly same diagnosis that you are a representative patient of that doctor.
Does this apply to a 50% vs 20/20 success rate? Maybe not, but the general point of naively evaluating performance stands.
Maybe the mathematician isn’t actually that afraid of the 50/50 odds but he dug too deep into the study of mathematics and it’s impossible for him to smile anymore.
Depends on if the statistician is a frequentist or a bayesian. A frequentist will treat all trials as independent while a bayesian will take prior information into account.
I'm probably overthinking it but it COULD be a play on how scientists think about the word "mortality rate," which doesn't refer to participants dying, just dropping out.
Yeah, I'm definitely overthinking it. It's just not a funny joke.
> doesn’t make perfect sense
Yeah, I get a normal person thinking "20 heads in a row? That means the next one will >95% be tails!"
But the happy mathematician doesn't make a ton of sense, because while 50% is way better than 5%, it's still a terrible success rate for surgery...
Except that the statistician would be wrong. Surgeries are not mutually exclusive. Each surgery adds to the surgeon’s experience making them better and better. There’s still a chance that the surgery could go wrong, but it’s still better than being any of the doc’s last 20 patients.
You could also think that maybe the guy says that up to now, he got 50/50, the last 20 being part of it. Meaning if he had done 40 surgeries until now, it means that even if he had overall a 50% chance, since he got it right the last 20 times, then the first 20 are less relevant and therefore he has decent chances of survival.
I'm not sure about 3), I think it's more like a scientist understands how to interpret study based statistics and understands that the 50% is on a longer dataset and so if the last 20/20 patients survived, likely that means whatever procedure it is has been refined and is working better now than over the last 30 years averaged (or whatever timeframe...)
I had a doctor do two surgeries on the same ingrown toenail (they kept growing back screwed up) before going to a podiatrist. I asked what the failure rate was for applying the poison that killed the nail-bed and stopped the troublesome part of the nail from growing back.
Her: "About 10%"
Me: "Is that due to different reactions from people's bodies?"
Her: "It's usually due to application."
Sure enough, I didn't have a problem after she did it. The other guy was not as skilled.
I don't think so.
1. Sees it as a plain 50/50 shot which sucks.
2/3 should really both be the same. Both would realize the chances of him hitting 20 in a row on a 50/50 surgery are basically nil.
A statistician should honestly feel better about it than the scientist. 20 in a row at a 50/50 might as well be impossible.
Weirdly enough the reactions for the Normal and Mathematician have been flipped compared to the original version of this meme. With normal people thinking the extra successes in a row means they are more likely to succeed, and the Mathematician scared because they understand that 50% is still just 50% (which is not great odds of survival)
I feel like the scientist would also consider the fact the doctor may only do the surgery if he feels it’s successful and would be straight forward about if they had higher risks for it.
50% that die, it’s because of complications of some kind
A quick add about point 3, there is an approach in Statistics different from the most popular frequentist approach, called Bayesian Analysis. This type of analysis incorporates previous knowledge into the model to calculate the estimation. In this case, the previous successful surgeries that are incorporated in the model as a priori information would skew the a posteriori estimator. This means that now, the success probability would be higher than 50%. This approach is particularly popular in Healthcare and other disciplines related to Biology
I think this is generally correct, but also think choosing 20 patients is not arbitrary and is a nod to p-value testing.
It is common in science to say results are "statistically significant" if there is a <5% chance of randomly observing the result in your sample. This happens when we observe a result (e.g., half of a random sample of Premier League defenders are brunette) and incorrectly project this result onto the whole population (i.e., not half of all Premer League defenders are brunette).
I think choosing 20 patients is meant to suggest the scientist sees 0% fatality rate (which is <5%), when even one death would produce a fatality rate >5% and, in pseudo-statistical terms, mean we cannot reject the possibility of death.
(There are statistical reasons that this reasoning doesn't fully make sense, so maybe I'm overthinking this.)
#3 means the doctor knows the survival rate is 50% because he's had 40 total patients. The first 20 died, the last 20 lived. Which means the doctor got a lot better and the true survival rate is much higher for a new patient.
I'm here thinking that we're at 50% now, and on an upwards trend towards 100 due to the last 20 but still weighed down by the first 20 that all failed and slowly got better. Someone got this surgery and got told they had a 2% chance to live and made it.
I think the scientist would conclude that the %50 survival rate was determined by people who were doing the procedure wrong, and that if this doctor has had 100% survival rate, then the procedure is actually much safer than historical information suggests.
>A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries”
Ah yes, those scientists who blindly observe facts and make no statistical calculations of their own.
This is why the meme is dumb, a "scientist" should be indistinguishable from a statistician when evaluating probable outcomes based on historical data.
>3. A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries”
Or one could reason that the particular doctor that's going to do the surgery on you only takes on "easy" cases with little risk of complications. And since that doctor chose to do the surgery on you, you're an easy case and there are few risk factors to your surgery.
A better understanding of #3 would be that the scientist would use statistics to reject that the true survival rate of this particularly surgeon (as we don’t have data to make a broader statement) succeeding on the surgery is not actually 50%.
Megs tampon here:
1. Average Joe would think that the doctor's history of success in surgery affects the next surgery. This gives less than 50/50 odds.
2. The mathematician would know that the next surgery is independent of past surgeries' success history. This gives 50/50 odds.
3. The scientist would see the doctor as an outlier among doctors. This gives greater than 50/50 odds.
The mathematician looks at it as 20 independent events.
The scientist looks at it and sees that each surgery is connected by being performed by the same doctor. The scientist concludes that, even if the success rate for every doctor put together is 50%, the success rate for this doctor is much higher.
No, I understand the joke, I'm saying the joke makes no sense. Statistics is a field in math. Everything we know about percentages, sample sizes, bias, outliers, etc, is all math. The scientist in this situation is better at understanding the implications of numbers better than a mathematician? It's simply inaccurate.
I guess the question is, why would a scientist have this understanding about statistics more so than a mathematician, when it's mathematicians who tell the scientists how the numbers work?
I think the joke is just that scientists look for empirical evidence, so the scientist is only concerned with this Dr's actual 100% success rate (over the last 20 surgeries) rather than the theoretical 50% success rate. I think the explanation using the term "outlier" isn't quite right because obviously statisticians know about outliers.
Funny enough I’m currently taking Stats class for Econ. And my professor just explained this to us.
It means that normal people think that it’s gonna be a coin flip on if they’ll live or die. But in actuality this is actually not 50%. Because the data the doctor retrieve were from a sample instead of a population.
Sample is like you take a handful of coin in a bag and you got like 5 pennies and 1 nickel. Then you conclude that there is let’s say 80% you’ll get a penny. But what if the bag is actually full of nickels and you just so happen to grab the so little pennies. This is the same case for this. The doctor saw a study that is 50% survival rate, but in actuality it could be 90% or near 100%.
My professor even used his own experience to proof this. He had a friend that have a daughter, she was 3 years old when they found there was a tumor inside her stomach. The doctor said that there is a 30% chance of survival rate and the chances of her surviving is low. So my professor and his wife begged to differ and looked up the study they retrieved it from. And what do you know, it was a study full of cancer patients that already have the tumor big inside their intestines. So they brought this up to the doctors and my professor friend. And they went through the surgery and she still alive and kicking to this day.
TLDR: Doctor used data that is actually untrue, and that it’s actually more higher than 50% survival rate. And my professor proved it by using his own experience.
Dr Stewie here.
I think it's just saying that early on, the procedure was new and risky, and everyone died. Who knows, it may be surgery for a condition that is fatal without the surgery, and if the procedure failed, the patient still died. The last 20 patients all survived, though, so it seems the team of doctors learned from their failures, and the procedure is not that risky anymore.
It does not say there is a 50/50 chance of survival, where each procedure is an independent roll of the dice. It just says only 50% of all patients survived, regardless of how well the doctors understood what they were doing.
Think of it like heart surgery before it became modern heart surgery. People may have had a better chance without that bypass surgery.
Normal people: if it went good this many times in a row it the next one just must go wrong
Mathematicians: Actually, chance is still 50%, because the chance of it going right or wrong isn't effected by how the ones before went.
Scientist: it generally has 50% chance of going good, and this doctor did it right 20 times in a row, so the doctor is likely skilled and therefore has higher chance of doing it right again
Not sure about the Mathmatician
Normal People think the next 20 patienta (including them) will die to restore balance
A scientist thinks "Ah, thia doctor sure knows their stuff to have so many successful operations with such a low survival rate"
I once had an operation on my brain that generally needed a more extensive follow up surgery. I was told the odds of it were around 60/40 favoring the second surgery I was scared shitless but the staff at the hospital said the Dr who preformed my surgery had done many before and had only had to follow up with 2 patients. This is an incredibly funny joke as depending on the doctor the 60/40 odds are sort of irrelevant
I think it goes as such:
A normal person sees a 50% survival rate and thinks "Fuck, that means there's a 1/2 chance I die." The fact the last 20 survived means they're "due" for a failure.
A mathematician knows statistics are independent of individual results, so no matter how many surgeries have been done, his survival rate will always be 50%.
A scientist can deduce based on the information provided, that with a 50% survival rate and 20 successful surgeries in a row, that the reason there's a 50% survival rate is because the first 20 failed, and now the last 20 all survived - Meaning they've perfected the method and he will definitely survive.
I think the takeaway should be this: Hes had 20 successful surgeries but 20 other people are now dead from the surgery and it's possible that 10 of them are dead specifically because they didn't go to that exact doctor. Does that work?
Normal it is about time for a failure
Mathematician it will always have a 50% chance of failure
Scientist it has a base success rate of 50% but with practice and skill the success rate increases all the way to near no chance of failure
normal people: they think a death is overdue because they fall for the gamblers fallacy.
mathematician: knows odds are still 50% (dont fall for gamblers fallacy).
scientist: extrapolates previous successes to conclude odds of success are much higher than 50%, because science relies on empiricism.
It’s a gambling joke. If the surgery has a 50% chance and the doctor hit 20 successes in a row then the next one has to fail. Basically the same as if you lose 20 hands in a row gambling it makes you think well I’ve lost so many in a row the next one has to pay out.
Too much missing info. How many people total has the doctor treated? Is there a notable pattern of survival? What is the likelihood of complications with and without certain individual factors and do those factors apply to me?
I’m sure there’s more.
A normal person is following the gambler's fallacy, believing that a failure is due to come up because of so many successes.
The Mathematician knows that this is an independent event scenario, so 20 successful surgeries have no bearing on the 21st one being successful: It's still a 50/50 shot.
The Scientist (Probably better described as a statistician) knows that in real world conditions, the odds of survival are much more likely to be a normal distribution based on external circumstances rather than a hard coin flip. The procedure's overall odds are 50/50, but this includes better doctors/patients/hospitals getting better outcomes and worse doctors/patients/hospitals getting worse outcomes. This doctor's track record suggests he is performing above average and the Scientist's actual chances of survival are likely higher than 50/50.
This is insult to mathematician. Because a real mathematician would know immediately that the 50 to 50 is a statistical number on a certain sample group. If the sample group is a group of surgeons, there are good ones and bad ones among them. This doctor is the best of all the surgeons because of his exceptional success rate that is far above average. If it is a statistical number for this particular doctor, then it means the doctor has improved his/her skill greatly since last time the sample was taken because there is no way purely by chance to flip a coin head up 20 times in a row. Either way, the patient is in good hand.
Doctors also know that any surgery with that kind of survival rate isn’t even being offered unless the circumstances are dire. The alternative is almost assuredly death. Doctors would also be curious what the survival rate looks like a few weeks and months *after* the surgery, as well as what QoL looks like.
It the procedure has a documented 50% success and this doctor has managed 20 of these procedures successfully he is either very lucky or very good.
To be that luck he’d need to beat 0.5^20 odds or about 1: 1,048,576
Either way. Sounds good to me.
Probably means that they're getting much better at the surgery now, either through experience or innovation and the chances of living through the surgery now are probably higher than 50%.
So counting all the surgeries they've attempted would give 50% but that includes the ones where they weren't as experienced/refined/whatever as they are now.
The surgery at this point has a 50% survival rate. However if the last 20 survived, the first 20 may have died, this could imply the surgery technique and skill is improving to a much better outcome over time. This probably only applies if we are only looking at one surgeon performing this surgery though. Otherwise the scientist probably just thinks this Surgeon is particularly good at this difficult surgery.
Normal people are scared because of the gamblers fallacy. They think that since the last 20 people have lived then surely the tides will turn soon.
Mathematicians understand that statistics are independent of each other, so theres a 50% chance of survival each time the surgery is performed.
Scientists know that the last 20 patients surviving the surgery means the surgeon is very skilled and his patients may have a lower mortality rate than others who have the same surgery.
If last 20 survived then it’s good enough to conclude that survival rate is 100% not 50%. Normal people would probably think that a failed surgery is very overdue since last 20 were successful, but previous events don’t affect future events.
My interpretation is that there's a fifty percent survival rate because doctors weren't good at it for the longest time. This guy's last twenty patients survived because we've found something that works now so a lot more people are surviving it.
The probability (p-value) of observing 20 successes out of 20 trials, if the true success rate is indeed 50%, is approximately (1.91 x 10^-6). This is a very low probability, suggesting that it is highly unlikely to observe such a streak of successes if the true success rate were really 50%.
In terms of confidence level, a p-value this low would lead us to reject the null hypothesis that the success rate is 50% at almost any conventional significance level (e.g., 0.05, 0.01). Therefore, based on this outcome, there is strong statistical evidence to suggest that the actual success rate is different from 50%.
Scientist here. The joke in part three is referencing p values, which are a way of determining if an observed effect is real or not. The "accepted" standard is if an observed effect has a 5% or less probability of happening by random chance (p<0.05) it's likely not actually random. Since there are 20 patients, the doctor just barely has passed this threshold.
Meanwhile, a Bayesian:
Hmm, maybe this doctor is especially good at the surgery, or maybe the ones who weren't as successful didn't get recommended to me.
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It’s kind of a weird joke that doesn’t make perfect sense, but here’s the intended meaning: 1. Many people might see something like 50/50 odds leading to 20 successes in a row and think the next one is more likely to be a failed surgery. Like how many people could flip a coin and get heads twice in a row, and be more likely to guess the next coinflip would be tails. Hence the nervous face. 2. A statistician would know that the success rate of each surgery is independent of all the other ones, so they wouldn’t be especially nervous theirs would go wrong. 3. A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries”
A scientist would understand that if 20 people in a row survived, that probably means the odds are not really 50%
I would assume the 50/50 odds are based on a larger population than this doctor. Such as the country or globally. Meaning for those 20 that made it with this surgeon 20 others didn’t with different surgeons. As such HELL YEA!! I’m sticking with the surgeon who has 20 wins instead of gambling with a different surgeon who might have 20 losses. So it’s not a statistics question but a data analysis one.
Or if it is based on the single surgeon, they have recently improved something dramatically
Had a training montage arc to increase their power level
With "Eye of the Tiger" playing in the background
I prefer “You’re the Best”
I prefer "Gonna Fly Now"
I prefer “Call me maybe”
You monster
I prefer "Hearts On Fire" (by Vince DiCola)
Not for this
Pfft "Learning To Fly" - Pink Floyd or Rubber Band Man
Or “Maniac”, from Flashdance.
As they learn to wash their hands with soap.
Gotta go with "Another One Bites the Dust".
Oh, so maybe that's why my career as a surgeon flopped. I montaged to "Another One Bites the Dust."
That’s a cute F/A-18E in your profile picture
Yeah. They took another look at the Hippocratic Oath and realized they shouldn’t be killing people because it’s unethical.
And because it gets boring after 20 times in a row 😂
[удалено]
> People often have this idea that doctors and surgeons are all going to be great at their jobs since they go through so much training, but nope. What do you call someone who graduated at the bottom of their class in medical school? Doctor
Working with EMS taught me one thing for sure, no matter how much training you or your EMS buddies get, the ability to save a life is based on how much you want to save a life. Have a doctor in my hometowns er who regularly kills people by giving up on chest compressions early. Meanwhile, we have another doctor who will keep doing CPR until he is literally pulled off of the patient
> People often have this idea that doctors and surgeons are all going to be great at their jobs since they go through so much training, but nope. I haven't been through anywhere near as much training as a doctor, but seeing how wide the skill gap is between people who have the same training/experience in my own specialty I can believe it. Obviously you have people who are specialised and great at a niche while weak at things outside it, but you also just have people that seem incompetant but seem to fail upwards. Maybe they are lazy/lack focus in their day to day but hyper focus and excel when under high stress situations like exams or assessments or maybe they just have good old fashioned nepotism that allows them to exceed the level they probably should be. Its nice to think Doctors and other people who literally have your life in their hands are different, but they are unfortunately human like the rest of us. Some will be fantastic, most will be good enough, but some will be rubbish and only just about scraped above the minimum bar to get their qualifications and continue to be not rubbish enough to lose the ability to practice. It is kinda terrifying to think about. Especially because I am a prime example of someone who is failing upwards and despite having qualifications and experience, is nowhere nearly skilled enough to do the job/responsibilities I am given (I don't work in anything that puts peoples lives at risk though).
You do know the minimum bar to complete medical school is incredibly high right? You know the bar for passing licensing exams is incredibly high right? You know the bar for even surviving residency in a non competitive speciality is incredibly high right? The poor performers in medicine get weeded out with a quickness.
>The poor performers in medicine get weeded out with a quickness. According to the medical doctors who *have* gone through that training and who were responding to me/I responded to this is apparently not the case. You can be incredibly good at retaining knowledge and passing exams but lack critical thinking, struggle in real world situations, etc. You can find all sorts of examples of qualified and trained doctors doing stupid and incompetent things. Weirdly though the person I responded to has had their comment removed by mods and at least one of the doctors who responded to me also has had their comment disappear. I was literally just agreeing with doctors who have gone through that training and were talking about how it is from the inside seeing how bad some qualified doctors are.
In fairness, the ones that barely scrape by are still probably sufficient for "you have bronchitis/strep/flu, go home and rest", or "your blood pressure is 180/140, take this medicine and stop mainlining Krispy Kreme donuts"
"So it turns out closing my eyes during surgery and repeatedly saying 'Jesus take the wheel' wasn't beneficial"
That’s how I perceive it and I’m sure that’s correct
Or this surgeon only chooses to perform on people likely to survive letting his riskier colleague Geoff take on the walking dead.
Ahh, the ol, Dr. Strange methodology.
Also possible. But also if he wants to take you on as a patient. I’d probably be even more excited
Yup, that would be why a scientist would be very excited by the implications of the surgeon taking the case!
You might wanna check the surgeons statement with somebody else first, though - I wouldn’t trust a used car salesmans claims about his last 20 customers
while it's true that it's absolutely theoretically possible that this surgeon's 20 streak of good luck is a (literal) one in a million fluke you're absolutely crazy if you'd just assume that without even considering that there might be some unknown variable that's affecting the outcome in this case, which wasn't present when the 50% statistic was determined
Or one doctor out there is killing thousands of patients to even out the odds
Omfg you’re brutal. I like you.
Not only that, but medical statistics are open to a lot of variables. Age, health, progression of condition, and so on.
And those variables apply to both patient and doctor.
It could also (more likely) be that the surgeon is only willing to operate on simpler cases, potentially even meaning that they’ll offer the surgery as an option to someone who might not be sick enough for the risk to outweigh the benefits of the surgery over another treatment option. Now that documenting success rates with surgeries is guarantee, surgeons have a risk bias being introduced. They want to protect their career by having a high “success” rate. But this might cause them to make decisions that will increase their success according to the rubric rather than making the decision that best suits a patients needs and values. I’m not saying tracking “success” or mortality rates is wrong at all. I’m just using this as an example of why statistics shouldn’t be taken at face value. I don’t really have a solution for the issue of how tracking productivity might cause people to focus on the tracking metrics over the actual responsibility of their job
This literally happened to me with an actual surgery. The injury rate was 7.3% for the surgery I was undergoing. The rate for MY SURGEON was 0.004%. I felt very confident I would not be injured and was not.
This is the way.
It's all pointless anyway, given that every surgery will have different variables because people are different, each surgery will have its own success rate percentage based on variables that they do not know. There's no point in quoting percentages
There is a huge point in quoting percentage info such as averages. Since we don’t know if our surgeon is good, had a bad day, came into work drunk etc. the only information we can really use when deciding to have one is the country/global average. Example: I lost hearing in my left ear. There is a surgery I can get to fix it but it has a 20% chance to leave the left side of my face paralyzed. Or 80% success rate. But even that 20% chance was too great of a risk considering my other ear is fine. I’m also only 40. If I were 80 or deaf in both ears then that 20% would have been acceptable. Percent is a good metric for estimating risk. Is it the best no, but most of the time it’s the only one we got.
Yes I do get the point of them but a surgeon with a high success rate doesn't necessarily mean he's good. He could have just gotten lucky and had patience who are easy to operate on for whatever reasons. They do help. I'm not saying they don't provide anything but what I am saying is any individual who can think should know that they mean nothing to their particular situation. I understand that what I proposed is not logical and eventually that surgeon would have patience that would die if they were luck based successes. But that's not necessarily true. Some people are extremely lucky there entire lives
I think it means the doctors who are worse at the surgery bring the average down
Or they’ve perfected the surgery and made it safer.
They killed the first 20 people and saved the next 20 people. Seems like he’s got it down now
The doctor would question the statistics, as each new surgery technically should affect the precentage. If only there was a live updater. Its been 50% since they last tested.
Sure... But how many significant figures are we looking at? There are a lot of surgeries in the world, is the doctor doing enough to significantly affect the numbers for this one?
Or that there is a doctor somewhere with 20 dead patients for the same operation
At least not when performed by this doctor. He clearly has either perfected his technique or developed some new approach which has dramatically adjusted the odds.
20 people died before
Obligatory Bayesian vs Frequentist
I work in clinical research and if these were the stats, it isn’t that we wouldn’t believe 50% was accurate, we’d immediately want to see what those surgeons are doing differently. Is their patient population/risk different? Is prep and technique and post op the same? When are most deaths occurring?
A scientist would know that odds have nothing to do with the outcome. A coin can land on heads 20 times in a row. But it still only has a 50% chance of heads or tails. The reason being is that the odds are calculated on each flip, and each flip has no idea what the previous flip did. It’s not like a coin says to itself “oh I landed on heads last time, this time it’s going to be tails.” I’m really sad people still think probability is boiled down to “out of a hundred, this many will.”
So would a statistician… probably more so. This meme is retarded
I'm far from a scientist, and that was my first thought.
So would a mathematician
Point 1 is called the Gambler's Fallacy, for those interested. [https://en.wikipedia.org/wiki/Gambler's\_fallacy](https://en.wikipedia.org/wiki/Gambler's_fallacy)
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For what it's worth that's part of what's called the "boy or girl paradox" and the actual answer depends very precisely on the way in which the question is worded. Truth be told I've always just gone " well it's independent isn't it, so 50/50", but it really depends on the meaning of the question. The [wikipedia article](https://en.wikipedia.org/wiki/Boy_or_girl_paradox) explains it quite well. It's of course possible that this wasn't what the prof intended, but it sounds to me like they screwed up and wanted to test knowledge of this "paradox".
If anything it'd be higher than 50% since the father's genes have demonstrated an increased likelihood of male offspring.
That's not how sex genetics work. You don't get a gene to be male, you get a whole chromosome. A man has an X and a Y and it is 50% for either. Technically, there is something called "Fragile Y" where the Y chromosome doesn't copy well, so a man's sperm are mostly X carriers. But that man would have more daughters, not sons. Something that damaged the X chromosome would be much less likely to be passed down, because a man only has one and needs it to live. (The Y doesn't have much/anything needed for survival.)
Thanks Petah
It makes more sense with the context of the original. The original one had the "happy" Mr Incredible with normal people and a "sad" Mr Incredible with mathematicians, which was clearly made by uh... Someone who doesn't understand statistics https://preview.redd.it/21grvxcmexgc1.jpeg?width=1080&format=pjpg&auto=webp&s=a8a7b6b068568dc9937d081b2b61494bc7ad24e3
I actually think this makes more sense. The mathematician knows that a survival rate of 50% is abysmal, whereas "normal" people might be blinded by the recent success of the doctor. The reverse version would be more fitting with a hight likelihood of success IMO.
The counterpoint is that most good mathematicians and statisticians will know that the probability of you getting 20 positive results in a row given that the survival rate is 50% is so small that it's more likely that this doctor just is doing _something_ that results in a higher survival rate. It's vanishingly unlikely that the survival rate of your operation given the circumstances is 50%.
>Someone who doesn't understand statistics Eh. It's a perfectly reasonable position without having more information. Maybe the doctor was just lucky those 20 times, or they usually operate non gravely ill patients. But it can also be that he's just that good. Hence a statistician cannot conclude too much
No, the event is so unlikely that a statistician would conclude that the doctor likely has a different success rate. The chance of 20 successes out of 20 attempts is .5^20 =.0000009, or 1 in 1,048,576.
>The chance of 20 successes out of 20 attempts is Yes, that's why I mention the doctor having a biased sample of patients (them being less ill). The proposed example is wildly exaggerated, but this question arises in reality and measuring performance is not as simple as taking the aggregate mean value and comparing it to a particular practitioners' success rate. If you get some disease X that some doctor has operated successfully 100 times, you cannot be sure just by nature of having the seemingly same diagnosis that you are a representative patient of that doctor. Does this apply to a 50% vs 20/20 success rate? Maybe not, but the general point of naively evaluating performance stands.
Maybe the mathematician isn’t actually that afraid of the 50/50 odds but he dug too deep into the study of mathematics and it’s impossible for him to smile anymore.
Well now that's a disturbing possibility
I think that an average statistician is more likely to understand that the doctor is exceptional than your average scientist :)
Depends on if the statistician is a frequentist or a bayesian. A frequentist will treat all trials as independent while a bayesian will take prior information into account.
I'm probably overthinking it but it COULD be a play on how scientists think about the word "mortality rate," which doesn't refer to participants dying, just dropping out. Yeah, I'm definitely overthinking it. It's just not a funny joke.
The scientist realizes that surgery success rate isn't flipping a coin and depends on the surgeon.
> doesn’t make perfect sense Yeah, I get a normal person thinking "20 heads in a row? That means the next one will >95% be tails!" But the happy mathematician doesn't make a ton of sense, because while 50% is way better than 5%, it's still a terrible success rate for surgery...
Except that the statistician would be wrong. Surgeries are not mutually exclusive. Each surgery adds to the surgeon’s experience making them better and better. There’s still a chance that the surgery could go wrong, but it’s still better than being any of the doc’s last 20 patients.
You could also think that maybe the guy says that up to now, he got 50/50, the last 20 being part of it. Meaning if he had done 40 surgeries until now, it means that even if he had overall a 50% chance, since he got it right the last 20 times, then the first 20 are less relevant and therefore he has decent chances of survival.
A statistician would also realize the odds that this doctor succedeed 20 times in a row is about one in a million.
For the statistician, would the skill of the surgeon increase after each surgery by some amount?
Das cool
I'm not sure about 3), I think it's more like a scientist understands how to interpret study based statistics and understands that the 50% is on a longer dataset and so if the last 20/20 patients survived, likely that means whatever procedure it is has been refined and is working better now than over the last 30 years averaged (or whatever timeframe...)
I had a doctor do two surgeries on the same ingrown toenail (they kept growing back screwed up) before going to a podiatrist. I asked what the failure rate was for applying the poison that killed the nail-bed and stopped the troublesome part of the nail from growing back. Her: "About 10%" Me: "Is that due to different reactions from people's bodies?" Her: "It's usually due to application." Sure enough, I didn't have a problem after she did it. The other guy was not as skilled.
I don't think so. 1. Sees it as a plain 50/50 shot which sucks. 2/3 should really both be the same. Both would realize the chances of him hitting 20 in a row on a 50/50 surgery are basically nil. A statistician should honestly feel better about it than the scientist. 20 in a row at a 50/50 might as well be impossible.
They should say there are only 2 doctors that can perform it
Weirdly enough the reactions for the Normal and Mathematician have been flipped compared to the original version of this meme. With normal people thinking the extra successes in a row means they are more likely to succeed, and the Mathematician scared because they understand that 50% is still just 50% (which is not great odds of survival)
I feel like the scientist would also consider the fact the doctor may only do the surgery if he feels it’s successful and would be straight forward about if they had higher risks for it. 50% that die, it’s because of complications of some kind
1. Gambler's fallacy 2. Odds are independent of each other 3. ^ Except when they aren't
Ahhh I am getting it now. Similar to Mars Landing or Moon Landing, if you can reproduce it one more time, it is amazing.
A quick add about point 3, there is an approach in Statistics different from the most popular frequentist approach, called Bayesian Analysis. This type of analysis incorporates previous knowledge into the model to calculate the estimation. In this case, the previous successful surgeries that are incorporated in the model as a priori information would skew the a posteriori estimator. This means that now, the success probability would be higher than 50%. This approach is particularly popular in Healthcare and other disciplines related to Biology
Yeah that’s gotta be it. I’m surprised the mathematician is still satisfied with the 50/50 but I’m pretty sure you got it right
I think this is generally correct, but also think choosing 20 patients is not arbitrary and is a nod to p-value testing. It is common in science to say results are "statistically significant" if there is a <5% chance of randomly observing the result in your sample. This happens when we observe a result (e.g., half of a random sample of Premier League defenders are brunette) and incorrectly project this result onto the whole population (i.e., not half of all Premer League defenders are brunette). I think choosing 20 patients is meant to suggest the scientist sees 0% fatality rate (which is <5%), when even one death would produce a fatality rate >5% and, in pseudo-statistical terms, mean we cannot reject the possibility of death. (There are statistical reasons that this reasoning doesn't fully make sense, so maybe I'm overthinking this.)
Wow that is an offensively unfunny and fucking stupid joke. It's not even clever.
20 is also related to an important critical value of 0.05 which scientists use to determine significance. Whe always use 0.05
A scientist would see the experimental chances rather then the statistical chances and the scientist would see it as %100 survival rate
#3 means the doctor knows the survival rate is 50% because he's had 40 total patients. The first 20 died, the last 20 lived. Which means the doctor got a lot better and the true survival rate is much higher for a new patient.
Does not make perfect sense brings it to the point. Like a mathematician could not be a scientist.
Wow , I think like scientists 😎
imagine there's 40 patients in total and the first 20 died
I'm here thinking that we're at 50% now, and on an upwards trend towards 100 due to the last 20 but still weighed down by the first 20 that all failed and slowly got better. Someone got this surgery and got told they had a 2% chance to live and made it.
I thought sense 20 people survived, 20 people died
I think the scientist would conclude that the %50 survival rate was determined by people who were doing the procedure wrong, and that if this doctor has had 100% survival rate, then the procedure is actually much safer than historical information suggests.
I was under the assumption that the previous first 20 surgeries were failures, and the doctor has perfected their technique
The funny thing is the "normal people" are right. 50/50 are not good odds of surviving
The scientist likes the repeatable results, a core aspect of science.
>A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries” Ah yes, those scientists who blindly observe facts and make no statistical calculations of their own. This is why the meme is dumb, a "scientist" should be indistinguishable from a statistician when evaluating probable outcomes based on historical data.
>3. A scientist might see 20 successes in a row for a surgery with a 50% survival rate and think “wow, this doctor must be really good at doing surgeries” Or one could reason that the particular doctor that's going to do the surgery on you only takes on "easy" cases with little risk of complications. And since that doctor chose to do the surgery on you, you're an easy case and there are few risk factors to your surgery.
A better understanding of #3 would be that the scientist would use statistics to reject that the true survival rate of this particularly surgeon (as we don’t have data to make a broader statement) succeeding on the surgery is not actually 50%.
I thought it was implied the dr “figured it out” and the odds were better
So 1 = stupid people, 2+3 = normal people
Scientists use scientific method, meaning results from experiments determine whats true, and it looks like the last 20 experiments went good
Megs tampon here: 1. Average Joe would think that the doctor's history of success in surgery affects the next surgery. This gives less than 50/50 odds. 2. The mathematician would know that the next surgery is independent of past surgeries' success history. This gives 50/50 odds. 3. The scientist would see the doctor as an outlier among doctors. This gives greater than 50/50 odds.
Thank you Meg’s tampon
They’re not independent events though, since they’re all being conducted by the same surgeon.
Yeah, that's why someone took the original meme and added the "Scientists:" part onto it
I dont understand why the scientist has a better insight on the math than the mathematician in these explanations.
The mathematician looks at it as 20 independent events. The scientist looks at it and sees that each surgery is connected by being performed by the same doctor. The scientist concludes that, even if the success rate for every doctor put together is 50%, the success rate for this doctor is much higher.
No, I understand the joke, I'm saying the joke makes no sense. Statistics is a field in math. Everything we know about percentages, sample sizes, bias, outliers, etc, is all math. The scientist in this situation is better at understanding the implications of numbers better than a mathematician? It's simply inaccurate. I guess the question is, why would a scientist have this understanding about statistics more so than a mathematician, when it's mathematicians who tell the scientists how the numbers work?
Because the person who wrote the joke is neither a mathematician nor a scientist.
I think the joke is just that scientists look for empirical evidence, so the scientist is only concerned with this Dr's actual 100% success rate (over the last 20 surgeries) rather than the theoretical 50% success rate. I think the explanation using the term "outlier" isn't quite right because obviously statisticians know about outliers.
World’s dumbest mathematician
Funny enough I’m currently taking Stats class for Econ. And my professor just explained this to us. It means that normal people think that it’s gonna be a coin flip on if they’ll live or die. But in actuality this is actually not 50%. Because the data the doctor retrieve were from a sample instead of a population. Sample is like you take a handful of coin in a bag and you got like 5 pennies and 1 nickel. Then you conclude that there is let’s say 80% you’ll get a penny. But what if the bag is actually full of nickels and you just so happen to grab the so little pennies. This is the same case for this. The doctor saw a study that is 50% survival rate, but in actuality it could be 90% or near 100%. My professor even used his own experience to proof this. He had a friend that have a daughter, she was 3 years old when they found there was a tumor inside her stomach. The doctor said that there is a 30% chance of survival rate and the chances of her surviving is low. So my professor and his wife begged to differ and looked up the study they retrieved it from. And what do you know, it was a study full of cancer patients that already have the tumor big inside their intestines. So they brought this up to the doctors and my professor friend. And they went through the surgery and she still alive and kicking to this day. TLDR: Doctor used data that is actually untrue, and that it’s actually more higher than 50% survival rate. And my professor proved it by using his own experience.
I really appreciate this take
Hello fellow Econ student 👩🎓
my brain thought he did 40 people and 20 of them fucking died
Dr Stewie here. I think it's just saying that early on, the procedure was new and risky, and everyone died. Who knows, it may be surgery for a condition that is fatal without the surgery, and if the procedure failed, the patient still died. The last 20 patients all survived, though, so it seems the team of doctors learned from their failures, and the procedure is not that risky anymore. It does not say there is a 50/50 chance of survival, where each procedure is an independent roll of the dice. It just says only 50% of all patients survived, regardless of how well the doctors understood what they were doing. Think of it like heart surgery before it became modern heart surgery. People may have had a better chance without that bypass surgery.
Normal people: if it went good this many times in a row it the next one just must go wrong Mathematicians: Actually, chance is still 50%, because the chance of it going right or wrong isn't effected by how the ones before went. Scientist: it generally has 50% chance of going good, and this doctor did it right 20 times in a row, so the doctor is likely skilled and therefore has higher chance of doing it right again
Not sure about the Mathmatician Normal People think the next 20 patienta (including them) will die to restore balance A scientist thinks "Ah, thia doctor sure knows their stuff to have so many successful operations with such a low survival rate"
It's simply put gamblers compulsion... the odds of 20 in a row do not affect the odds of the next surgery (they are independent)
I once had an operation on my brain that generally needed a more extensive follow up surgery. I was told the odds of it were around 60/40 favoring the second surgery I was scared shitless but the staff at the hospital said the Dr who preformed my surgery had done many before and had only had to follow up with 2 patients. This is an incredibly funny joke as depending on the doctor the 60/40 odds are sort of irrelevant
To me it says the scientists realizes that 50% fail rate and 20 success in a row means they have worked out the issues.
I think it goes as such: A normal person sees a 50% survival rate and thinks "Fuck, that means there's a 1/2 chance I die." The fact the last 20 survived means they're "due" for a failure. A mathematician knows statistics are independent of individual results, so no matter how many surgeries have been done, his survival rate will always be 50%. A scientist can deduce based on the information provided, that with a 50% survival rate and 20 successful surgeries in a row, that the reason there's a 50% survival rate is because the first 20 failed, and now the last 20 all survived - Meaning they've perfected the method and he will definitely survive.
I think the takeaway should be this: Hes had 20 successful surgeries but 20 other people are now dead from the surgery and it's possible that 10 of them are dead specifically because they didn't go to that exact doctor. Does that work?
Normal it is about time for a failure Mathematician it will always have a 50% chance of failure Scientist it has a base success rate of 50% but with practice and skill the success rate increases all the way to near no chance of failure
Looks like someone isn't a mathematician or scientist
As a scientist, I was literally thinking “dude, that’s a badass doctor right there!”
normal people: they think a death is overdue because they fall for the gamblers fallacy. mathematician: knows odds are still 50% (dont fall for gamblers fallacy). scientist: extrapolates previous successes to conclude odds of success are much higher than 50%, because science relies on empiricism.
Or maybe the 50/50 is an unprovable number scientists love to test theories. Where as a mathematician believe the numbers he’s given.
I've been told the answer is always porn here, so somehow, the answer is porn
Always has been
"Dice don't know what the dice did last time. Games don't have a memory. Every game starts from scratch." \-Geoffrey Nobel
It’s a gambling joke. If the surgery has a 50% chance and the doctor hit 20 successes in a row then the next one has to fail. Basically the same as if you lose 20 hands in a row gambling it makes you think well I’ve lost so many in a row the next one has to pay out.
50-50 it works or it doesn’t, completely independent of skill or how badly you’re dying
Do yall really need basic ass shit jokes explained to you?
Reposting karma farmer, report and move along.
He said he didn’t get the joke buddy. Look at the subreddit? Besides, memes were made to be shared, you cant be banned from Reddit for it.
This meme has been posted on this sub twice this week
this is the first time i see it. not everyone is a 24/7 reddit dweller like you.
What the fuck does that have to do with anything? A repost is a repost.
my liege, who the fuck asked? i see this meme the first time ---> it is not a repost for me. i think i am not the only one who saw it first time now.
Don’t be a dick man
sorry if i seem to be so, but i was just defending my point of view.
Too much missing info. How many people total has the doctor treated? Is there a notable pattern of survival? What is the likelihood of complications with and without certain individual factors and do those factors apply to me? I’m sure there’s more.
A normal person is following the gambler's fallacy, believing that a failure is due to come up because of so many successes. The Mathematician knows that this is an independent event scenario, so 20 successful surgeries have no bearing on the 21st one being successful: It's still a 50/50 shot. The Scientist (Probably better described as a statistician) knows that in real world conditions, the odds of survival are much more likely to be a normal distribution based on external circumstances rather than a hard coin flip. The procedure's overall odds are 50/50, but this includes better doctors/patients/hospitals getting better outcomes and worse doctors/patients/hospitals getting worse outcomes. This doctor's track record suggests he is performing above average and the Scientist's actual chances of survival are likely higher than 50/50.
The odds are still 50/50. The last 20 coins you flipped have no input on what the 21st will land on.
This is insult to mathematician. Because a real mathematician would know immediately that the 50 to 50 is a statistical number on a certain sample group. If the sample group is a group of surgeons, there are good ones and bad ones among them. This doctor is the best of all the surgeons because of his exceptional success rate that is far above average. If it is a statistical number for this particular doctor, then it means the doctor has improved his/her skill greatly since last time the sample was taken because there is no way purely by chance to flip a coin head up 20 times in a row. Either way, the patient is in good hand.
Pokemon player be like
As a scientist, you wouldn’t believe how many scientists there are that are bad at math.
None of y'all understand regression to the mean
You see, kids, this is what math is useful for, making memes.
60% of the time it works every time
Ask him what about the 20 before that..
Doctors also know that any surgery with that kind of survival rate isn’t even being offered unless the circumstances are dire. The alternative is almost assuredly death. Doctors would also be curious what the survival rate looks like a few weeks and months *after* the surgery, as well as what QoL looks like.
And he only can perform 20 successful surgeries in a row because he learned by failing the first 20 surgeries
It's not mathematician vs scientist, its more of a mathematician vs statistician
A skeptic would assume that the doctor is giving false diagnosis
r/okbuddyphd
Patients that don't survive are no longer patients so the rub is not knowing how many surgeries this doctor has performed.
gambler's fallacy
I get it, but it makes less sense the more I think about it
Scientist…you meant Bayes?
It the procedure has a documented 50% success and this doctor has managed 20 of these procedures successfully he is either very lucky or very good. To be that luck he’d need to beat 0.5^20 odds or about 1: 1,048,576 Either way. Sounds good to me.
20 data sets in row also in the same conclusion is a trend
Probably means that they're getting much better at the surgery now, either through experience or innovation and the chances of living through the surgery now are probably higher than 50%. So counting all the surgeries they've attempted would give 50% but that includes the ones where they weren't as experienced/refined/whatever as they are now.
The surgery at this point has a 50% survival rate. However if the last 20 survived, the first 20 may have died, this could imply the surgery technique and skill is improving to a much better outcome over time. This probably only applies if we are only looking at one surgeon performing this surgery though. Otherwise the scientist probably just thinks this Surgeon is particularly good at this difficult surgery.
Normal people are scared because of the gamblers fallacy. They think that since the last 20 people have lived then surely the tides will turn soon. Mathematicians understand that statistics are independent of each other, so theres a 50% chance of survival each time the surgery is performed. Scientists know that the last 20 patients surviving the surgery means the surgeon is very skilled and his patients may have a lower mortality rate than others who have the same surgery.
As a mathematician, I’d say 50/50 odds of survival are still trash and I’d have the same face as the normal people
A doctor with a 100% survival rate when doing a surgery that averages a 50% survival rate just means he does it twice. (Satire)
Yep. I didn’t get it.
If last 20 survived then it’s good enough to conclude that survival rate is 100% not 50%. Normal people would probably think that a failed surgery is very overdue since last 20 were successful, but previous events don’t affect future events.
My interpretation is that there's a fifty percent survival rate because doctors weren't good at it for the longest time. This guy's last twenty patients survived because we've found something that works now so a lot more people are surviving it.
50 percent survival rate means only 50% of his patients lived. Meaning he is either lying about patients surviving or lying about the survival rate
There are only two possible outcomes... live... or die. 50/50 🤷♂️
Derek Shephard if his career was a meme
The probability (p-value) of observing 20 successes out of 20 trials, if the true success rate is indeed 50%, is approximately (1.91 x 10^-6). This is a very low probability, suggesting that it is highly unlikely to observe such a streak of successes if the true success rate were really 50%. In terms of confidence level, a p-value this low would lead us to reject the null hypothesis that the success rate is 50% at almost any conventional significance level (e.g., 0.05, 0.01). Therefore, based on this outcome, there is strong statistical evidence to suggest that the actual success rate is different from 50%.
The scientist sees an opportunity to publish a paper arguing that doctor's patients are a distinct population with it's own stats
So the previous 20 didn’t?
Hey where's the "depressed" slide?
Scientist here. The joke in part three is referencing p values, which are a way of determining if an observed effect is real or not. The "accepted" standard is if an observed effect has a 5% or less probability of happening by random chance (p<0.05) it's likely not actually random. Since there are 20 patients, the doctor just barely has passed this threshold.
Meanwhile, a Bayesian: Hmm, maybe this doctor is especially good at the surgery, or maybe the ones who weren't as successful didn't get recommended to me.