We are talking about a big difference between accepting a random event 100% of the time and making a choice according to values.
Suppose that every day, random jobs are assigned to you. What difference will there be after 100 jobs if you accept all of them or if you accept half of the jobs that go in the direction that is favorable to you and decline half of the ones that go away?Subjectivity The blue 0s are groups where the peak mountain did not make a proactive choice, and the orange 40s are groups where the peak mountain half-refused; being near 0 is a situation of mediocrity, lack of character, and failure to build a carrier.
- The effect of having Refusal Options is very significant. Once you have a clear values axis, you can move in the direction that matches your values by simply selecting and choosing random events that appear on a daily basis based on whether or not to move in the direction of your values axis. Compared to the distribution of results for those who did not make selection due to circumstances, the difference is obvious after only 100 steps.
In situations where a minority group benefits, it is very advantageous to be in the minority. The reason is that if you are near the origin, the probability of profiting is low.
Suppose two random jobs are assigned to you on a daily basis; how is it different if you choose to accept the one that goes in your favor out of the two, compared to the āif itās not favorable, donāt accept itā case above? The one who chose between two options to undertake (blue) had an average value around 55. The expected value is higher for the one who chooses to perform the preferred task. Both choices are two options, ādo/not do Task Aā and āTask A/Task B,ā but the expectation value is higher when there are multiple task options. This is due to the higher expected value of ādo the more convenientā (blue: expected value 0.56) than ādo not do when it is inconvenientā (orange: expected value 0.40) for the single task.
In addition, of course, the three choices of ādo Task A/do Task B/do not do Task Aā are even better. Related studies: Quantity of choices and quality of decision making.
Original Idea: It would be interesting to compare the distribution of a simple random walk with that of choosing between two random alternatives that are closer to oneās values
Experimental condition, ārandom workā is a standard normal distribution with mean 0 and variance 1.
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