crabman

Does playing hard to get work? AB testing for romance

I found this post useful, because it contains practical ideas about how to perform personal experiments in dating.

I think you are confused about how statistics work. Student's T-test is a frequentist thing, while in some places you say that you have aprior which suggests you want to do bayesian analysis.

The sentence

My prior is 70% that the H1 is true (conditional on null being false).

makes no sense because of the part in parentheses.

Introduction to Cartesian Frames

According to your interpretation of controllables, in , isn't controllable, because it contains , which can be found in another row. By the original definition, it's controllable.

Bet On Biden

Is there a simple guide on how to bet on Biden if I already have Ethereum and I don't live in the US? It seems I can do it on Augur and FTX, but both platforms seem very complicated.

verloren's Shortform

You might be interested in https://www.facebook.com/groups/1781724435404945/ - a facebook group where rich rationalists set up $10-$100 tasks for others to do. However, only about 25% of the tasks are doable if you don't live in the US.

Also, I'll pay you $15 if you fix this issue https://github.com/orgzly/orgzly-android/issues/287 in the Android app called Orgzly, which is an implementation of emacs org-mode for android, and make the owner accept it into the main branch or whatever it is they use that gets merged into the app on google play.

Turns Out Interruptions Are Bad, Who Knew?

Do you write in Roam using a phone? Do you read literature sources on it as well?

Philosophy of Therapy

When I saw the title "Philosophy of therapy", I hoped to find some answers to the following questions:

- How to think about therapy given Dodo bird verdict?
- How to think about therapy given that approximately 50% of all published studies in it fail to replicate?
- Given 1 and 2 and the fact that therapy works for some reason and the fact that different types of therapeautic theories contradict each other, therapy must work not only because because it improves the patient's map of the territory, but also by another mechanism. So, what's going on here? Maybe it improves the patient's map of the territory despite the incorrect information in therapeautic theories?

Inaccessible finely tuned RNG in humans?

My method is to come up with a phrase or find a phrase written somewhere nearby, count the syllables or letters, and take this value modulo the number of bins. For the topicstarter's poll, I found a sentence on a whiteboard near myself, counted its letters modulo 10, got 5, so I voted for 30%, because the bins were like 20% - 30% - 50%.

What is complexity science? (Not computational complexity theory) How useful is it? What areas is it related to?

How useful is their vocabulary and their set of ideas to understand the real world, not as a professional researcher, but just as a rationalist?

What is complexity science? (Not computational complexity theory) How useful is it? What areas is it related to?

Complexity theory seems to be a rarely used synonym for complexity science. Although, it's used in the title of one of the books. I've mistakenly used "complexity theory" too many times in my question. I've just fixed that.

Regarding some courses/primers/introductions, I found them by following links and citations from other complexity science related things and by using connectedpapers.com to find similar books/articles, not just by googling complexity science. (Except for the classcentral courses, but those talk about dynamic systems, chaos, and fractals, so they are probably also on-topic) So they most probably support the idea of complexity science. You can also Ctrl+F "emerg" to find the use of the word emergence in them and see that they talk about complexity science.

To be clear, I've checked *Understanding complexity by Scott E. Page - the book contains lectures and is published by Princeton university press* and *Complexity: a guided tour - Mitchell 2011 published by Oxford university press* and they definitely talk about emergence, self-organization and contain other vocab associated with complexity science.

What is your null hypothesis? Nowhere does your post says that. I suspect you don't know what a null hypothesis is.

From your post and your comment, I infer that you want to find the probability of "intentionally reducing reactivity and affection for the first three dates will increase attraction in partners". That doesn't work well with bayesian analysis. Instead you should try to get a posterior distribution over the value of how much it increases attraction.

I think if you want to do the bayesian data analysis, then one of the simplest ways you could model your situation is as follows.

If you PHTG, you achieve sex (or whatever it is you're after, but I'll just say sex for simplicity) with probability p∈(0, 1). If you don't PHTG, you achieve sex with probability q∈(0, 1). Currently, you don't know the values of q and r but you have a prior distribution p(q, r) over them. In this prior p(q, r), q and r are not necessarily independent. On the opposite, I would expect that they correlate (with respect to the prior p(q, r)) very strongly, because if you often achieve sex with one strategy, probably you'll also be able to do that with the other strategy, and if you can't achieve sex with one strategy, probably you can't with the other. Next, you will go and do the experiments (go on dates and randomly choose whether to PHTG). An experiment is like tossing a biased coin. If you are PHTG, you are tossing a coin which lands on heads with probability q. If you are not PHTG, you are tossing a coin which lands on heads with probability r. After n experimental results e1,…,en, you update your distribution over the values q and r: p(q,r∣e1,…,en)=p(e1,…,en∣q,r)p(q,r)p(e1,…,en)=p(e1∣q,r)p(e2∣q,r)…p(en∣q,r)p(q,r)p(e1,…,en) and this is the result you get. I think this models represents your situation fairly well.

I don't know what prior p(q, r) you should choose in order to have it fairly close to your actualy beliefs while at the same time making the computation tractable. A simplification you can try is imagining that prior to the experimental data, q and r are totally independent from each other. Then your situation is simply two separate situations, in each you are trying to estimate the biasedness of a coin. Then you take the prior of q to be a beta distribution, and the prior of r to be a beta distribution as well. Then you open "Data analysis a bayesian tutorial - Sivia Skilling" (can be found on libgen) page 14 example 1 "is this a fair coin?" and do whatever it says. Another thing you could probably do is come up with some kind piecewise-constant prior p(q, r) manually and perform the bayesian analysis by simulating everything on the computer rather than tinkering with integrals on paper. Formally, this is called Monte Carlo integration.

Also, instead of treating the outcomes as binary (sex or no-sex), you could treat them as real numbers which represent how well it went. I think this way you'll need less experiments to get a conclusion. For this case, you can read "Bayesian Estimation Supersedes the t Test - Kruschke 2012". That paper describes how to do bayesian analysis when you have two groups (treatment and control) and you want to measure what the treatment does if it does anything.