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arjie 16 hours ago

Oh I really enjoyed this one.

Got a quick insight about how penicillin works: interferes with cell-wall building which is a destroy and recreate process by preventing the recreate part.

Got a quick view into the scientific process and communication: Fleming focused on the insight - penicillium kills staphylococcus - and left out the circuitous detail. This is important so that the big win here is very clear.

And got an insight into human nature and memory: Fleming didn’t tell the accidental contamination story until much later. It could possibly be even an idea someone else might have come up with which then took root in his mind (ironic haha!)

The communication aspect reminds me of Mendel’s far too perfect ratios for his pea plants. That kind of “repeat till difference clear” statistics would be decried today but perhaps that was to communicate rather than to determine.

And finally, I really enjoy reading about human process innovation because I think it’s a big factor in how Humanity grows. The lab notebook has to be some kind of star performer here - Fleming’s notes allow us to look back like this.

When I experiment with things, I naturally lean to keeping notes on my test protocol, observations, and results. But not because of some personal genius. It’s just the standard way I was taught as a child in our science labs.

I won’t claim to the rigor of a microbiology lab but even just the process notes help a lot, which is useful since I’m just testing molecules on myself.

stevenwoo 13 hours ago | parent | next [-]

If you are not familiar with more of Mendel or plant biology, he got extremely lucky in picking a two chromosome species. The next plant he picked had more than two chromosome types so he spent the rest of his life hitting his head against the wall - obvious to us but him not having a theory and expertise with microscopes to explain his pea results hampered him greatly beyond his initial pea plant studies.

dexwiz 10 hours ago | parent [-]

What do you mean by a two chromosome species? A quick google says pea plants have 14 chromosomes. I only looked because I had never heard of a species only having two chromosomes. Do you mean the traits he was selecting for only had two alleles?

dekhn 9 hours ago | parent | next [-]

The traits he picked- hope I get this detail pedantically correct: had only two alleles, each allele had an obvious phenotype controlled mostly by that gene, the two phenotypes were binary (no intermediate "half-wrinkled-half-smooth"). and all segregated independently (different chromosomes, or far enough that the linkage was extremely weak). I remember my high school teacher speculating he inspected many different phenotypes and then reported his results on the final ones he picked where the results were nice.

Unfortunately, most modern genotypes and phenotypes in humans don't follow these patterns, and over the years, genetics devloped an entire vocabulary and physical model to explain them, although at a fairly abstract level. None of it made any sense to me so I follow the biophysics/molecular biology approach which tends to consider many more underlying physical details

There's a related story, https://review.ucsc.edu/spring04/bio-debate.html and https://review.ucsc.edu/spring04/twoversions.html which shows how different fields think about the genotype/phenotype relationship. Grinding up steering wheels to figure out how they work...

dexwiz 9 hours ago | parent [-]

Yeah that was my understanding. Most things have multiple genes controlling them. Like there is no single eye or hair color gene.

ahazred8ta 2 hours ago | parent | prev | next [-]

Diploid. Peas have 7 pairs of chromosomes. Many types of plants have multiple (polyploid) copies of each chromosome, and you will not discover the classic Mendelian dominant-recessive pattern by studying them. Mendel lucked out by studying a diploid species. https://duckduckgo.com/?q=polyploid&ia=web

stevenwoo 10 hours ago | parent | prev [-]

Right, my bad for wrong terminology as biology nor botany is not my speciality either. I was thinking along the lines of XY for humans, then the ordinary two row, two column chart used to teach the basics of Mendel with pea plants and dominant/recessive non polygenic traits in introductory biology classes.

kcexn 6 hours ago | parent | prev | next [-]

It's a shame that Fleming misremembered his process of discovery and created a myth of accidental discovery.

I like the Root-Bernstein narrative more. That in the monotonous execution of routine experiments for something unrelated an unusual observation 'forced' them to discover penicillins antibacterial properties.

Not an accidental discovery by good fortune in a serendipitous sense. An accidental discovery of a brute force exhaustive search. The narrative of we spent months meticulously examining hundreds of samples is less romantic, but is one that supports the importance of funding scientific inquiry.

We won't make progress by hoping people leave culture plates out on window sills. We make progress when we fund meticulous exhaustive efforts of discovery.

Joker_vD 16 hours ago | parent | prev | next [-]

> Mendel’s far too perfect ratios for his pea plants.

"Remember, if you flip a coin 200 times and it comes heads up exactly 100 times, the chances are the coin is actually unfair. You should expect to see something like 93 or 107 instead".

fainpul 15 hours ago | parent | next [-]

Isn't 100 / 100 the most likely outcome for a fair coin? Sure it's unlikely that you hit exactly that result, but every single other result is even less likely.

What I'm trying to say: if you get 100 / 100, that's not a sign of an unfair coin, it's the strongest sign for a fair coin you can get.

shakow 15 hours ago | parent | next [-]

> every single other result is even less likely.

But the summed probability of the “not too far away results” is much higher, i.e. P([93, 107]\{100}) > P([100]).

So if you only shoot 100/100 with your coin, that's definitely weird.

tshaddox 15 hours ago | parent | next [-]

Okay, but it doesn't make sense to arbitrarily group together some results and compare the probability of getting any 1 result in that group to getting 1 particular result outside of that group.

You could just as easily say "you should be suspicious if you flip a coin 200 times and get exactly 93 heads, because it's far more likely to get between 99 and 187 heads."

wat10000 14 hours ago | parent [-]

It's suspicious when it lands on something that people might be biased towards.

For example, you take the top five cards, and you get a royal flush of diamonds in ascending order. In theory, this sequence is no more or less probable than any other sequence being taken from a randomly shuffled deck. But given that this sequence has special significance to people, there's a very good reason to think that this indicates that the deck is not randomly shuffled.

In theory terms, you can't just look at the probability of getting this result from a fair coin (or deck or whatever). You have to look at that probability, and the probability that the coin (deck etc.) is biased, and that a biased coin would produce the outcome you got.

If you flip a coin that feels and appears perfectly ordinary and you get exactly 100 heads and 100 tails, you should still be pretty confident that it's unbiased. If you ask somebody else to flip a coin 200 times, and you can't actually see them, and you know they're lazy, and they come back and report exactly 100/100, that's a good indicator they didn't do the flips.

tshaddox 10 hours ago | parent [-]

> It's suspicious when it lands on something that people might be biased towards.

Eh, this only makes sense if you're incorporating information about who set up the experiment in your statistical model. If you somehow knew that there's a 50% probability that you were given a fair coin and a 50% probability that you were given an unfair coin that lands on the opposite side of its previous flip 90% of the time, then yes, you could incorporate this sort of knowledge into your analysis of your single trial of 200 flips.

wat10000 8 hours ago | parent [-]

If you don’t have any notion of how likely the coin is to be biased or how it might be biased then you just can’t do the analysis at all.

tshaddox 2 hours ago | parent [-]

You can certainly do the frequentist analysis without any regard to the distribution of coins from which your coin was sampled. I’m not well studied on this stuff, but I believe the typical frequentist calculation would give the same results as the typical Bayesian analysis with a uniform prior distribution on “probability of each flip being heads.”

fainpul 15 hours ago | parent | prev | next [-]

> So if you only shoot 100/100 with your coin, that's definitely weird.

Not if you only try once.

shakow 15 hours ago | parent | next [-]

Even if you shoot only once, you still have a higher chance of hitting something slightly off the middle than the perfect 100/100. And this because that's one point-precise result (100/100) vs. a cumulated range of individually less-probable results, but more probable when taken as a whole.

For a fair coin, hitting 100/100 is ~5%, vs. ~30% falling in [97; 103] \ {100}. You can simulate here: https://www.omnicalculator.com/statistics/coin-flip-probabil...

tshaddox 14 hours ago | parent | next [-]

> you still have a higher chance of hitting something slightly off the middle than the perfect 100/100

That's because "something slightly off the middle" is a large group of possible results. Of course you can assemble a group of possible results that has a higher likelihood than a single result (even the most likely single result!). But you could make the same argument for any single result, including one of the results in your "slightly off the middle" group. Did you get 97 heads? Well you'd have a higher likelihood of getting between 98 and 103 heads. In fact, for any result you get, it would have been more likely to get some other result! :D

zdragnar 14 hours ago | parent [-]

> But you could make the same argument for any single result

Isn't that the point? The odds of getting the "most likely result" are lower than the odds of getting not the most likely result. Therefore, getting exactly 100/100 heads and tails would be unlikely!

tshaddox 13 hours ago | parent | next [-]

But as I said, getting any one specific result is less likely than getting another other possible result. And the disparity in likelihoods is greater for any one specific result other than the 50% split.

alwa 12 hours ago | parent | prev [-]

I think the disagreement is about what that unlikeliness implies. "Aha! You got any result? Clearly you're lying!"... I'm not sure how far that gets you.

There's probably a dorm-quality insight there about the supreme unlikeliness of being, though: out of all the possible universes, this one, etc...

zdragnar 10 hours ago | parent [-]

Let's look at the original quote:

> "Remember, if you flip a coin 200 times and it comes heads up exactly 100 times, the chances are the coin is actually unfair. You should expect to see something like 93 or 107 instead".

Inverting the statement makes it read something like this:

You are more likely to not get 100/100 than you are to get exactly 100/100

...which is exactly what I was saying. Nobody is arguing that there is a single value that might be more likely than 100/100. Rather, the argument is that a 100/100 result is suspiciously fair.

e12e 13 hours ago | parent | prev [-]

Should that be 25% for 97..193 excluding 100?

shakow 12 hours ago | parent [-]

“[97; 103] \ {100}” means the interval [97; 103] without the set {100}; so no, still ~30%.

kalaksi 15 hours ago | parent | prev [-]

I'm sorry, but try what once? 200 flips once?

dredmorbius 6 hours ago | parent [-]

In statistics, various examples (e.g., coin flips) often stand in for other activities which might prove expensive or infeasible to make repeated tries of.

For "coin flips", read: human lives, financial investments, scientific observations, historical observations (how many distinct historical analogues are available to you), dating (see, e.g., "the secretary problem" or similar optimal stopping / search bounding problems).

With sufficiently low-numbered trial phenomena, statistics gets weird. A classic example would be the anthropic principle: how is it that the Universe is so perfectly suited for human beings, a life-form which can contemplate why the Universe it so perfectly suited for it? Well, if the Universe were not so suited ... we wouldn't be here to ponder that question. The US judge Richard Posner made a similar observation in his book "Catastrophe: Risk and Response" tackles the common objection to doomsday predictions that all have so far proved false. But then, of all the worlds in which a mass extinction event has wiped out all life prior to the emergence of a technologically-advanced species, there would be no (indegenous) witnesses to the fact. We are only here to ponder that question because utter annihilation did not occur. As Posner writes:

By definition, all but the last doomsday prediction is false. Yet it does not follow, as many seem to think, that all doomsday predictions must be false; what follow is only that all such predictions but one are false.

-Richard A. Posner, Catastrophe: Risk and Response, p. 13.

<https://archive.org/details/catastropheriskr00posn/page/13/m...>

grraaaaahhh 10 hours ago | parent | prev [-]

>But the summed probability of the “not too far away results” is much higher, i.e. P([93, 107]\{100}) > P([100]).

That's true of every result. If you're using this to conclude you have a weird coin then every coin is weird.

ptrl600 5 hours ago | parent | prev | next [-]

Low kolmogorov complexity equals suspicious

voakbasda 15 hours ago | parent | prev | next [-]

I would guess that a single trial of 200 flips can be treated as one event, so getting 100/100 is but one outcome. It may be the most likely individual outcome, but the odds of getting that exact result feel less likely than all of the other possible outcomes. The 100/100 case should be seen the most over repeated trials, but only marginally over other nearby results.

Intuitively, this seems right to me, but sometime statistics do not follow intuition.

dooglius 15 hours ago | parent | prev | next [-]

"fair coin" refers to both the probability of heads and tails being equal (which is still justified) as well as the trials being independent (unlikely with 100/200; more likely the "coin" is some imperfect PRNG in a loop)

tshaddox 14 hours ago | parent [-]

> more likely the "coin" is some imperfect PRNG in a loop

"More likely"? How can you even estimate the likelihood of the coin being "an imperfect PRNG" based on a single trial of 200 flips?

dooglius 14 hours ago | parent | next [-]

You can use combinatorics to calculate the likelihood. If your PRNG is in a cycle of length N in its state space (assuming N>200), and half the state space corresponds to heads (vs tails), then the likelihood would be (N/2 choose 100)^2/(N choose 200) versus your baseline likelihood (for a truly random coin) of (200 choose 100)/2^200.

Graphing here https://www.wolframalpha.com/input?i=graph+%28%28N%2F2+choos... and it does look like it's only a slight improvement in likelihood, so I did overstate the claim. A more interesting case would be to look at some self-correcting physical process.

ajuc 14 hours ago | parent | prev [-]

Bayesian vs frequentist in a nutshell :)

If a student was tasked with determining some physical constant with an experiment and they got it exactly right to 20th decimal place - I'll check their data twice or thrice. Just saying. You continue believing it was the most likely value ;)

buildsjets 10 hours ago | parent | prev | next [-]

A truly fair coin would never land heads or tails. It would land standing on it's edge, every single time.

Joker_vD 15 hours ago | parent | prev [-]

Well, yes. But the expected deviation from the mean is still ≈7.07. And the probability that the outcome will be either 93/107 or 107/93 is (slightly) higher than the outcome being exactly 100.

fainpul 15 hours ago | parent | next [-]

But those are 2 results. 100 / 100 is more likely than 93 / 107 (or any other specific result) is what I'm saying.

paddleon 15 hours ago | parent | next [-]

You can tell the difference between

93 heads, 107 tails and

93 tails, 107 heads

but not between

100 heads, 100 tails and

100 tails, 100 heads.

So while those are two results (93/107 and 107/93), they really only count as two separate outcomes if you pre-specify that the first number is heads.

If instead you consider symmetries, where there are 2 ways to get 93/107 and only one wall to get 100/100, then you have more likelihood for the 93/107 outcome because you have two ways to get it.

an hour ago | parent [-]
[deleted]
kalaksi 15 hours ago | parent | prev | next [-]

I don't think that makes 100 / 100 the most likely result if you flip a coin 200 times. It's not about 100 / 100 vs. another single possible result. It's about 100 / 100 vs. NOT 100 / 100, which includes all other possible results other than 100 / 100.

andoando 11 hours ago | parent [-]

If you flip a coin 200 times, and repeat that a billion times, 100/100 will be more likely than any other ratio.

It will be a bell curve with 100/100 as the peak

Joker_vD 15 hours ago | parent | prev [-]

Depends what you count as a result, I guess. "There is exactly N flips of a single kind" is also a viable definition, just as "The exact sequence of flips was x_0, x_1, ... x_199" is.

eviks 15 hours ago | parent | prev [-]

Why not go one abstraction further and go expected deviation from deviation? Probably the word "expected" plays a mind trick? "Expected" doesn't mean the probability increases, the easiest way to understand it is just by looking at the probability distribution function chart for coin tosses - you'll immediately see that mean has the highest chance of happenning, so exactly 100 is the most likely outcome

munchbunny 15 hours ago | parent | prev | next [-]

The chance of exactly 100 heads from 200 fair coin flips is approximately 5-6%. Qualitatively, that's not particularly strong evidence for an unfair coin if you did only one trial.

You could also argue that 100 out of 200 on a fair coin is more likely than any other specific outcome, such as 93/200, so if the argument is that the coin is "too perfect", you then also have to consider the possibility that the coin is somehow biased to produce 93/200 much more often than anything else, vs. 100/200.

nearbuy 2 hours ago | parent [-]

There is also no way to weight a coin that makes it more likely to get 100/200 than a fair coin.

n1b0m 15 hours ago | parent | prev [-]

In a real-world scenario, if you saw a result significantly far from 100 (like 150 heads), you might suspect the coin is unfair. However, seeing exactly 100 heads gives no reason to suspect the coin is unfair; it's the result most consistent with a fair coin.

awkward 13 hours ago | parent | prev [-]

So many other good details that get to how impossibly multivariate biology research is, like the need to have several days at the exact temperature.

It's not uncommon for results in biology to have this kind of snag in reproducibility even now. Sometimes it's due to attributing variations to something like "steady hands at the bench", but other times it can even be a deliberate attempt to prevent rivals from duplicating a process before it can be patented and privatized.

microtherion 11 hours ago | parent [-]

cf The Harvard Law: "Under controlled conditions of light, temperature, humidity, and nutrition, the organism will do as it damn well pleases."