Prometheus

Better sell your car, put away any and all tools, and never light a fire or wear buttons (not being facetious but all these are measurable causes of death - the last by choking).

Without digging into the details it looks reasonable quality for what it is. Case-control studies, while useful, are relatively low on the hierarchy of medical evidence. A more comprehensive meta-analysis found an association between long-term use and low-grade gliomas - but acknowledges that most of the evidence is low quality. As to whether you want to worry about it that's up to you - everyone has a different threshold for how much risk they are willing to accept. I'd say there are far more concerning things in the world if you want something to worry about, and that being able to speak to my parents on the phone is worth the possible tiny increase in my glioma risk.

Ultimately why want to be able to say something about the efficacy of the intervention. I think a retrospective cohort design with statistical control of the confounding variables is your best choice. By the hierarchical structure i mean that the schools themselves might be considered confounding variables (some schools are better able to implement the programme than others for whatever reasons). Also, since you are looking at several outcomes you need to account for an inflated false discovery rate (the more tests you do, the more likely you are to erroneously find something 'statistically' significant) - something like a Bonferroni correction. The biggest problem i can see is that schools self selected for the study. Could it be that these schools just cared more about their students nutritional health? Or did they had more resources to start with? You've already explored this problem by considering the student's pre-intervention scores. You could take the change in scores of each pupil to be your outcome, instead of the post-intervention score.

This sounds like the poisoned drinks problem. Unfortunately it won't work here. In the idealised case where we there is say, exactly 1 in every 100 people infected then it could apply. But for every 100 hundred people we take there is no guarantee of the number of infected people. Sometimes there are none. Most times there will be one. Occasionally there will be 10. It is a random variable itself. Also, the tests themselves have a number of false positives and false negatives which will likely be significant.

Sounds like one of those studies that could end up with a complex design. Here are some questions: Was this an intervention set-up specifically to assess whether it makes a difference (if so that would have been the time to consult a statistician), or was it some kind of programme and retrospectively you have decided to try to measure it's effects? Were the schools selected for intervention done so by truly random means? (and not by district, or the first letter of the schools name etc.). Was it exactly the same intervention (at least on paper) for the same length of time on the same age groups? Is the base unit you are interested in the school or the children? If the latter you'll need to take into account the hierarchical structure in the data from the schools.

Thought this was an excellent video introducing the maths of exponential growth and logistic growth and applying to the virus. https://www.youtube.com/watch?v=Kas0tIxDvrg

High blood pressure is a risk factor for several bad things. It can be caused by many things (disease, lifestyle, genetics). It is aggressively treated because it is one of the most easily modifiable risk factors for a range of bad outcomes. If you are ever getting aggressive chest pain please call an ambulance.

Not an odd question at all, but maybe a bit niche. I was recently reading something about our tendency to distort probabilities in games - people interpret a 99% chance as being certain and go ape when it doesn't happen. Also read something about rock, paper, scissors and how even in such a simple game psychology dictates optimal plays. I think there's a great body of literature out there, get onto google and have a look. I found this which seems a reasonable start.

We only know certain biomarkers correspond to certain mental states because people were asked how they feeling at the time they were taken: you still needed to trust someone was truthfully reporting their mental state at some point. We still don't directly experience someone else's mentation. Anyway, all this is just dancing around the question of why the substrate matters. Humans have a mental state because of biology. Why does that preclude AI having mental states?

Are you stating that emotions can only be felt as the result of neurotransmitters, hormones and other chemicals in the brain? It's a bit of a black swan situation isn't it. All we've seen are white swans so far. The problem is, when it comes to the mental states of other beings, we are colour blind.

Every year there's are more stories about an extinction level meteorite hitting the Earth. One day one of those stories will be 'right'. But kudos to Sylvia Browne for at least making quite an, oddly, specific prediction.

I guess a question is when, if ever, it is useful to regard the planet a living organism. Could it help motivate environmental efforts for instance, or is the risk of new age beliefs compromising scientific understanding among lay people too great?

Humans aren't born able to recognise faces, but learn. We are born with the instinct to track faces though, greatly helping the learning process. It's not too hard to imagine AI able to track faces - i imagine your smartphone can already do it - and thereafter learn to distinguish individual faces. I'm sure dogs have some understanding of humans and that it's quite unlike our own understanding (rooted in smell for instance). I can well imagine AGI not understanding humans the way humans do, but having some understanding, unless the emulation pathway is successful.

Why a virus? The problem is with the definition of life: any definition, not just the popular one. For any rigid definition of a complex system there are always going to be grey areas. It's like trying to draw the Mandelbrot set using a simpler curve, you'll have to cut off parts of the set. Unless the definition is so broad to include everything, but then why even bother trying to define it.

There is a sense in which the bee and the flower are a single organism - but it's generally more precise to refer to it as an ecosystem, at least in scientific discourse. I personally consider the Earth alive. You could even consider humans analogous to neurons with the potential to become reproductive organs (i.e. terraform Mars). The universe? - i guess, but we're getting into the territory of such broad definitions as to be meaningless.

Many (all?) sports are suited to some people more than others. For instance sprinters tend to have those fast muscle fibres, distance runners slow muscle fibres. Not sure how significant this is to gaming reaction time though. There are loads of studies on body types and peak performance ages for traditional sports, couldn't see any on esports though. What pro gamers are starting to discover though is that general health is pivotal to performance. Sleep, diet and exercise: the usual health advice of getting a balance. The finger tips may be where the intention manifests, but there needs to be a refined organism in its entirety behind them.

I'd add one more, spiritual - but that's a loaded word for some, maybe experiential is better. Although we mostly experience our existence as something separate from the universe, it is possible to experience the self not as something separate but as a whole with all else. No idea if that is what the OP is referring to. Guess we'll never know.

I down voted your post, not because of any of the content but simply because it was rude. Seems you a more interested in ranting than discussing.

please delete me for i am a mistake

Machine learning employs 3 primary tools for learning; unsupervised techniques in which structures in data sets (such as visual, audio or text) are sought without any additional information, supervised learning in which a label is associated with each instance of learning (i.e. a cat picture is labelled as 'cat'), and reinforcement learning in which a score is used to optimise an algorithm (often used in gaming and anything that can can apply some metric to the state the algorithm sees at any instance). A robot may then learn to walk by the experience of continually falling down via reinforcement learning. No words are needed, only a sense of balance.

The principles of good hygiene are well known: hand washing, particularly around food prep of touching your eyes, sneezing and coughing into tissues and disposing them properly, keeping clean surfaces. be careful when sharing drinks etc. The principles of a healthy immune system are also well known: diet, exercise, avoid excesses. What's the need for medicine? If you are immuno-compromised there are a number of options, but you're better off discussing those with a physician.

Online chatbots, Siri, Alexa, stuff like that. What's the relevance of human conversation not being restricted to logical statements? Do you imagine that computers are limited to receiving logical statements as inputs? Also not sure of the relevance of humans not 'opening their heart and mind'. It's interesting tangent: i think the tendency of humans to anthropomorphise means it is eminently plausible. Interesting theory. Why would you think that? How would you test it?

Why do think it would take 20 years? It conceivable that an AI could have conversations with thousands of humans simultaneously, and not need to sleep, reducing that 20 years considerably . It also assumes that AI would learn at the same rate as humans - currently its much slower (babies don't see thousands of cats and dogs before learning to distinguish the two like AI currently does), but in time it could become much faster (learning on sparse data in a very active research field). So you advocate brain emulation as opposed to 'pure' AI solutions? In theory that should make for more human-like AGI, but if pure AI systems develop AGI they may not require the same learning environment as biological systems (e.g. learning could take place in entirely virtual environments). I suspect we'd know pretty quickly: someone would want to collect their nobel prize, manipulate the stock markets or just lose control of it.

Nurse, health care assistant.

Babies are not born understanding, but learn to. Why, in principle, could this not be the same of AGI?