Bayesian inference is a method of statistical inference in which Bayes' theorem is used to calculate a probability of a hypothesis, given prior evidence. The one thing that is most important is that the more conditions something has to be filled (that is not 100%) the less likely it is to be true. Used a lot in game theory and even in daily life decisions subconsciously.
When you only need one success, even with 100 failures, like in job hunting. It's the reverse survivorship bias: you have a total expectation to fail before you succeed. IT's too tricky becuase it's invisible, but neither is it normal to expect mroe than the world can offer! Motivational impact is very strange here.
For some spice you can see: probabilistic non-God argument