> We apparently get enough protein due daily consumption and the avg sporty person doesn't need protein powder.
I don't know what that means. The amount of protein people get varies dramatically. Chicken is a remarkably efficient way to get protein. Greek yogurt is also pretty good.
If you haven't measured your protein intake (with an app like myfitnesspal) you should try it.
I always thought I was a pretty knowledgable person when it came to nutrition and my eating habits competely changed when I bothered to look up the calorie and macro count of everything I ate. I also dropped 40 pounds and put on a lot of muscle.
This comment may unnecessarily discourage people from using metformin.
- There is no evidence linking metformin to PSP, let alone a causal relationship.
- PSP is also very rare, prevalence ~ 7 per 100,000 [1].
- Metformin is used by 100+ million people [2].
- It has been safely prescribed for type 2 diabetes since the late 1950s [2].
Metformin is a highly effective and widely used medication. It would be unfortunate for people to avoid it based on speculative claims. If there’s specific evidence suggesting metformin as a risk factor for PSP, I’d be interested, but the leap from "mitochondrial complex I inhibition is associated with PSP" to "metformin causes PSP" is unwarranted.
As for the prophylactic use comment: we are all going to decay and die, trying to mitigate those risks with metformin is not unreasonable. There is evidence supporting its potential benefits, though some of these may reflect its established role in managing diabetes. (talk to your doctor, etc.)
> the leap from "mitochondrial complex I inhibition is associated with PSP" to "metformin causes PSP" is unwarranted
The mechanism of action is relatively straightforward: the inhibition is caused by a building up oxides within the mitochondria, which makes them less efficient at producing energy. And if the mitochondria go long enough without a mitochondrial antioxidant clearing out the oxides, they eventually die. And if enough of the mitochondria within your brain die, you get PSP.
My best guess as to the reason we haven't seen an association between PSP and metformin is that metformin is actually a mitochondrial type I adaptogen rather than a mitochondrial type I inhibitor. I'm definitely not telling people not to take it, but if you are then I think setting a couple Google scholar alerts would be prudent.
Not sure why this is downvoted. I settled with spreadsheets after trying out lots of such trackers. The frustration in your comment, I can feel. A lots of similar comments also reflecting the same about spreadsheets.
When people walk into a restaurant - fast food, slow food - especially before COVID, do you see people go to the bathroom to wash their hands before the meal? That never happens.
I've never seen it happen either - and I live in Poland, though I haven't seen it in my various visits to China, Germany and the UK either. Who actually does go into the restaurant bathroom specifically to wash their hands before the meal?
Three simple habits that have (anecdotally) cut down on colds for me:
* wear a mask in crowded environments where showing my face doesn't buy me anything (I don't wear one at work, but do at the grocery store or airport)
* wash hands before eating (or at least use hand sanitizer)
* grip the exit handle of the bathroom with a paper towel and dispose of it on exit
Not exactly double blind demonstrated but low cost and this year has been much better than last (which may also be due to my immune system having caught back up, too, so YMMV)
I do - it just makes sense if you are riding public transport or touching stuff that isn’t as clean as you’d think. Like your phone, wallet, keys, backpack, shoe laces, pant pockets, etc. Not obsessively, but if I haven’t washed my hands in a few hours or feel they are dirty I wash them before eating.
Spanish here. I do it all the time. I even carry a small bottle of alcohol in case I go to a place where I can't wash my hands first.
I would say most people do wash their hands here, however I have seen everything. From people not washing them to people using the toilet, not washing them, and then sitting on the table for lunch.
I usually carry a bottle of hand sanitizer to clean my hands before meals. I started doing this even before the pandemic, to avoid getting sick with the common cold.
A good number of people do this in my city: when I go on public transit, I see a fair number of commuters with a hand sanitizer bottle clipped to their bag with a carabiner. Many people also have a bottle in their pockets or purse.
I know you're coming from a good place, but the 'most people I meet don't understand this' line about statistics is quite arrogant. Most people you meet are fully capable of understanding statistics; you should do a better job of explaining it when it comes up, or maybe you are the one who misunderstands. After all, most statisticians thought Marilyn vos Savant was wrong about the goats too...
You don't have to be on the internet for long to see:
- "Polls are useless, they only sampled a few thousand people"
- "Why do we need the crime figures adjusted for the age/income/etc groups? Just gimme the raw truth!"
Have to say, I think stats are the least well taught area in the math curriculum. Most people by far have no clue what Simpson's or Berkson's paradoxes are. Most people do not have the critical sense when presented with stats to ask questions like "how was the data collected" or "does it show what we think it shows".
I just don't see it, tough ironically I don't have stats to back it up.
You don't have to be on the Internet long to see flat-earthers or any number of asinine ways of thinking. You can't stretch discrete observations from a supremely massive sample size into "most people".
Gee, if only there was some kind of rigorous and well understood process for determining how to transform discrete observations according to how representative they are, such that we could build a model for a larger population.
Something like that would be very useful for political decision, so perhaps we could name it after the latin word for "of the state"…
Also, etymonline makes a pretty convincing case that statisticum refers to the behavior of administrators, not to the concept of the administration, with the -ist- specifically indicating a person.
It's definitely arrogant. But after much experience trying to explain these things to people, I'm more and more convinced it's not just "if you just put it the right way they will understand". Sure, they will nod politely and pretend to understand, and may even do a passable job of reciting it, but once its cast in a slightly different light they are just as confused.
Much as with reading and writing, I think it takes an active imagination and a long slog of unlearning to trust logic (the "ought to" thinking that shields one from reality) and coming to terms with the race not being to the swift, etc, and that these effects can be quantified.
It's not that some people are incapable of it. Much like literal literacy has reached rates of 99.9 % in parts of the world, I'm convinced statistical literacy can too. But when your teacher is not statistically literate (which I hypothesise they are not, generally speaking), they will not pass that on to you. They will not give you examples where the race is not to the swift. They will not point out when things seem to happen within regular variation and when they seem to be due to assignable causes. They will not observe the battle against entropy in seating choices in the classroom. They will not point out potential confounders in propensity associations. They will not treat student performance as a sample from a hypothetical population. They will not grade multiple-choice questions on KL divergence, although that would be far more useful. I could go on but I think you get the point.
Yet to be clear, I'm not talking about just applying statistical techniques and tools. I'm talking about being able to follow a basic argument that rests on things like "yes I know they are a fantastic founder but startups fail 90 % of the time and so will they" or "if the ordinary variation between bus arrivals is 5–15 minutes and we have waited 20 minutes then there is something specific that put the bus we are waiting for into a different population." These are not obvious things to many people.
This is not a personal failure – it is a lack of role models and teachers. I wouldn't have considered myself statistically literate until recently, and only thanks to accidentally reading the right books. I wouldn't even have known what I was missing were it not for that!
I suspect it will take a few generations to really get it going.
If someone would donate me large amounts of money I would love to actively research this subject, come up with reliable and valid scales to measure statistical literacy, and so on. But in the meantime I can only think in my spare time and sometimes write about it online.
What resources would you recommend for someone who wants to improve their statistical literacy? You mention reading the right books, I'd appreciate it if you could give a short list, if you have time.
I am not the person you asked, but I have been on a similar path to improve my statistical literacy. For context, I am fairly good at math generally (used to be a math major in college decades ago; didn't do particularly well though I did graduate) but always managed to get myself extremely confused when it comes to statistics.
In terms of books: there are a few good ones aimed for the general public, such as The Signal and The Noise. How to Measure Anything: Finding the Value of Intangibles in Business is a good book of applying statistical thinking in a practical setting, though it wouldn't help you wrap your brain around things like the Monty Hall problem.
The one book that really made things click for me was this:
Probability Theory: The Logic of Science by E. T. Jaynes
This book is a bit more math-heavy, but I think anyone with a working background in a science or engineering field (including software engineering) should be able to get the important fundamental idea out of the book.
You don't need to completely comprehend all the details in math (I surely didn't); it is enough to have a high-level understanding of how the formulas are structured at the high level. But you do need enough math (for example, an intuitive understanding of logarithm) for the book to be useful.
I second both The Signal and the Noise as well as How to Measure Anything. I also mentioned upthread Willful Ignorance.
I think perhaps the best bang for your buck could be Wheeler's Understanding Variation -- but that is based mainly on vague memory and skimming the table of contents. I plan on writing a proper review of that book in the coming year to make certain it is what I remember it to be.
I think the earlier works by Taleb also touch on this (Fooled by Randomness seems to have it in the title).
But then I strongly recommend branching out to places where these fundamentals are used, to cement them:
- Anything popular by Deming (e.g. The New Economics)
- Anything less popular by Deming (e.g. Some Theory of Sampling)
- Moneyball
- Theory of Probability (de Finetti)
- Causality (Pearl)
- Applied Survival Analysis
- Analysis of Extremal Events
- Regression Modeling with Actuarial and Financial Applications
The more theoretical and applied books are less casual reads, obviously. They also happen to be the directions in which I have gone -- you may have more luck picking your own direction for where to apply and practice your intuition.
Edit: Oh and while I don't have a specific book recommendation because none of the ones I read I have good opinions on, something on combinatorics helps with getting a grasp on the general smell of entropy and simpler problems like Monty Hall.
Not my experience at all. Just one example: try talking to physicians about false discovery rates; even those who do not profit from state-of-the art screening methods. Incorporating Bayesian methods is even a struggle for statisticians. It is a stuggle for me.
The Monty hall problem is a great example of something I’ve been educated into believing, rationalizing, whatever you want to call it…but I would still never claim I “understand it.” I think that’s maybe the source of disagreement here, there are many truly unintuitive outcomes of statistics that are not “understood” by most people in the most respectful sense of the word, even if we’ve been educated into knowing the formula, knowing how to come to the right answer, etc.
It’s like in chess, I know that the Sicilian is a good opening, that I’m supposed to play a6 in the najdorf, but I absolutely do not “understand” the Najdorf, and I do think it’s fundamentally past the limit of most humans understanding.
This is not at all true, and I think it's an example of what statisticians have to fight against in order to explain anything. Most people have an almost religious belief that inferences drawn from statistics should be intuitive, when they are often often extremely counterintuitive.
> After all, most statisticians thought Marilyn vos Savant was wrong about the goats too...
This is the opposite of the argument that you're making. Here you're saying that probability is so confusing and counterintuitive that even the experts get it wrong.
My point was that the experts were blinded by arrogance.
Even back then most ( almost all? ) statisticians were capable of understanding the monte hall problem. Yet they just assumed that a woman was wrong when she explained something that didn’t match their intuition. Instead of stopping to think, they let their arrogance take over and just assumed they were right.
My experience is that most people don't understand statistics and can be pretty easily mislead. That includes myself, with my only defense being that I'm at least aware statistics don't intuitively make sense and either ignore arguments based on them or if absolutely necessary invest the extra time to properly understand.
Most people either don't realize this is necessary or don't have the background to do it even if they did, in my experience.
I'm not surprised by the statement 'most people i meet don't understand this'. More than 50 percent of people I meet are less educated. Its statisticly evident.
I might be over reaching but in fact what comes across as arrogance is just an example of statistical illiteracy.
Most (>> 50 percent of) people are very good at detecting patterns. People are very bad at averaging numbers of events, because the detected patterns stand out so much and are implicitly and unconsciously exaggerated.
An example. "in my city people drive like crazy" in fact means: this week i was a lot on the road and i saw 2 out of 500 cars that did not follow the rules and there was even one honking. It 'felt' like crazy traffic but in fact it was not.
The vast majority of people are not that great at statistics. Even something as banal as "correlation is not causation, and can often be explained by a common cause" will blow a fair few minds (e.g. telling most people that old chestnut about how the murder rate is correlated with ice cream sales).
“Financial derivatives” and “downside is limited” should never appear in the same sentence without strong conditions on what sorts of derivatives/ combos of them
I think people in the thread are mistakenly conflating the idea of buying options with writing options to sell, the latter of which can have unlimited downside
Failure to learn seems almost synonymous with overfitting. It’s the failure to distinguish noise from signal due to lack of data (or just lack of imagination and ability to quickly see the general pattern, or even that there might be one).
That would indeed be a nice use of LLMs, although for mathematics I wouldn’t feel I could trust them not to warp the meaning badly. You’d probably have to check each generation carefully by hand.
This happened to me in a grant application. We had written a web application that did a homomorphic encryption based calculation of molecular weight to demonstrate that HE could be used to build federated learning models for chemical libraries.
Our reviewers told us that machine learning on encrypted data was impossible. We had the citations and the working model to refute them. Very frustrating.
What was the end result? I was almost roped into a project like this, encrypted ML for biology applications. It was definitely possible, but it seemed too slow to be worthwhile. Other federated learning projects shut down because it was wayy more efficient on a single cluster, and that was without the HE tax. I also have no idea if you can practically do HE matrix operations on a TPU or GPU or CPU SIMD at least; presumably that's something the research would cover.
Then again I didn't test very much because they also wanted it to be the proof of work for a blockchain, a possibility that I didn't discount but also figured it'd be extremely hard and I wasn't the guy to do it.
Yep - cells would die. ...UNTIL they accrue enough dna damage to accidentally either:
- create a new way to generate thymidine
- fall into a proliferation strategy that no longer needs thymidine
Human cells did the same thing and created checkpoints to preclude malignant growth. There are a number of checkpoints already employed in your own bodies. But if you accrue enough DNA damage, you can get around each of those checkpoints (and get cancer):
- IF too much DNA damage, then die
- IF divided too many times, then die
- IF committed to die, actually die
But if a cell collects enough damage, it can get around ALL of the checkpoints. And evolution has shown us that there is no perfect watcher of the watchmen. Still pretty cool to create a new checkpoint this way.
If I was in an environment where such strong mutations can happen in a single generation of non-reproducing cells, I'd ve very worried about the health of my original cells.
Epigenetic modifications, such as methylation, are made to DNA by specific proteins. These modifications alter the transcription process from DNA to RNA, which in turn affects protein expression. This includes the expression of the proteins responsible for epigenetic changes themselves. In essence, the proteins that modify DNA also control the expression of their own building instructions through a feedback loop.
I guess that feels a bit like a von neumann machine to me, but I'm not sure the analogy is super helpful.
I don't know what that means. The amount of protein people get varies dramatically. Chicken is a remarkably efficient way to get protein. Greek yogurt is also pretty good.
If you haven't measured your protein intake (with an app like myfitnesspal) you should try it.
I always thought I was a pretty knowledgable person when it came to nutrition and my eating habits competely changed when I bothered to look up the calorie and macro count of everything I ate. I also dropped 40 pounds and put on a lot of muscle.
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