Correlation is linear. Many causal functions can be non-linear.
Think of medicine. X is the dosage, Y is the improvement of health. If the dose is too low, you will get no response. If the does is within a good range, health improves. If the does is too high, you will begin to get even sicker. If data was gathered all along this inverted parabola, the correlation might be zero. But there is still a causal relationship between health and dosage.
Thus you can have causation without correlation.
You can probably think of many such functions with diminishing or negative returns as the dosage increases, e.g. years of education vs. lifetime earnings.
Whether you see a positive, negative, or null correlation can depend on where you sample from the response function. In the "real world" data might be bunched up around certain regions of the response function. Thus for the "average person/instance" you can determine if there is a correlation or not, and then say this is basically the causal effect (for the average person/instance).
But if you want accuracy and precision over concision you will use a more complex model.
Concise models are better memes than complex models, however, and so we are flooded with linear models or binary models.
The only app you will ever need is "Google Sheets".
I started using it ~3 years ago as a time-sheet to track my work, activities, sleep, mood etc. I tried to do what you did - see how X impacts my mood and look for trends. Here's some of my findings over the past three years in that regard:
You learn by doing it.
Find someone you like (or who likes you) and start dating them!
Without dating apps:
With dating apps:
I know this isn't an "economisty" answer but it's pretty solid wisdom as far as I'm concerned. Also note this advice is geared toward long term relationships, not hookups. If you want to date for hookups instead you can checkout the many pickup artist websites.
WRT "who is still left in the dating pool" there are always some fraction of people who just broke up, or moved, or are still looking for the right guy/gal. As you get older there are fewer good single people, but they are also less choosy, and thus easier to get. Remember, you also stand out from the competition more when there are fewer good people.
Many of the other comments deal with thought experiments rather than looking at the reality of how "many worlds" is USED. From my point of view as a non-physicist it seems to primarily be used as psuedo-science "woo" - a revival of mystery and awe under the cloak of scientific authority. A kind of paradoxical mysticism for non-religious people, or fans of "science-ism".
An agent might act differently from MISUNDERSTANDING many worlds theory. Or by paying more attention to it. Psychological "priming" is real ansd powerful.
The answer by TAG below is case in point. For someone committed to a belief in determinism or fatalism, having a manyworlds theory in mind may buttress that belief.
I guess the actionable version is to develop transferable skills, abilities, wealth, or social capital that are highly valued by many different tribes.
Then you have the leverage to flit from one to the next, and not care about standing up for any particular tribe.
However, the game to acquire wealth, social capital, and valued skills is basically the game that we are all playing and has lots of competition. The only way to "opt out" is to join a local monopoly (i.e. a tribe). Also, in the real world, tribes often "loan us resources" to develop our skills, capital, etc. in exchange for "joining" the tribe.
I find this very true.
In fact, portraying a STRONGER identity often is met more easily results in better responses. The trick is that you can be strategic about it. By selecting between "personas" or "roles" you can select what kind of responses you want to get.
I find it helpful to think about the different situations I am in (work meetings, studying in cafes, meeting friends, etc.), and then think about "what is the most ideal response I could get" - and think about "what kind of person / action would provoke that kind of response?" Then, for the given situation make sure that everything is coherent - appearance, energy level, behaviors, speech cadence, etc.
Coherence is very powerful.
We already do this when we have a "work self" and a "home self". But for most of our activities it is not pre-planned. We just want to be "ourselves" - i.e. not have to strategically prepare for each situation.
As for "social identity theory" and feeling attacked, I don't think KYIS quite applies. When you are part of a tribe or subculture or whatever, there are several factors at play. (1) Defending the tribe may gain you status in the tribe. (2) Allowing attacks on fellow tribe-members to go unprovoked may put you personally at risk as well - thus the tribe makes it a value to protect fellow tribe-members.
KYIS may mean "don't join any tribes". Or more realistically - only feel kinship or trust toward those you personally know, not any abstract larger categories of people. Some would argue that this is how China used to work. However, as societies scale up in size, we typically do join social groups with abstract myths that bind people together, provide standards, and allow coordination among strangers.
Anyway, I guess it gets pretty complex as you unpack it. I suppose if you have skills that are in demand by many people, you do not need to be "married" to any one tribe, nation, or company. You can flit from one to the next if the current one falls. This may cause locals to mistrust you (e.g. the hatred for "globalists") which lowers your status locally, but if your skills are valuable enough, you won't mind too much.
So, the ultimate way to KYIS - be very valuable to many different groups of people. This may be from transferable skills, a great personality, or just a very strong and wide social network.
Does anyone really track the marginal utility of their possible investment this way? Utilons - sure. But ROI on status? ROI on "warm fuzzies"?
Also, this assumes we have good estimates of the ROI on all our options. Where do these estimates come from? In the real world, we often seem to spread our bets - constantly playing a game of multi-armed bandit with concept drift.
Can you explain what you mean by the problem of job training?
You mean job vs. career vs. calling?
If by "job training" you mean maximizing short-run over long-run earnings, I agree with you. But for that reason, if you move the "slider" toward a longer payoff period, then the schools will be incentivized to teach more fundamental skills, not short-term "job training".
On the other hand, sometimes people just need to get their foot in the door to get up and running. As they accumulate savings, on the job experience, professional networks, etc. even a good "first job" can give a lifetime boost.
A lot of people I grew up with have the "cold start" or "failure to launch" problem, where they never get into a good-enough paying job and just spin their wheels as the years go by, never gaining traction. For them even getting a foot in the door will get the ball rolling.
Nearly all education should be funded by income sharing agreements.
E1 = student's expected income without the credential / training (for the next n years).
E2 = student's expected income with the credentia / training (over the next n years). Machine learning can estimate this separately for each student.
C = cost of the program
R = Percent of income above E1 that student must pay back = (E2-E1)/C
Give students a list of majors / courses / coaches / apprenticeships, etc. with an estimate of expected income E2 and rate of repayment R.
Obviously, rich students could still pay out of pocket up front (since they are nearly guaranteed a high income, they might not want to give a percent away).