First of all I must say, that this is not correct to ask “what is the probability for ME to receive “A” grade”. Because this is not a random event. The result of my grade depends on my skills and teacher’s evaluation – and these factors are not random. The definition of probability is related to random events or random variables, etc. We can only say about the probability of “randomly picked student will receive “A” grade” or “randomly picked exam/research work will be evaluated with A”, etc.
However, we can statistically calculate, what’s a chance to receive “A” grade based on previous statistics of grades. For doing this, we have to choose a period, for example, one semester, and consider all marks that I received (from “F” to “A”). Calculate the amount of “A” and the amount of all marks. Then the ratio between these numbers is the part of “A” grades in all grades, which might be interpret as the probability of receiving “A” grade.
Surely, all students in my class will not arrive at the same probability assessment that I have, because in case of each student there are individual numbers of all grades and “A” grades.
A subjective probability is the probability determined from observations at some person. This probability is different from individual to individual. Actually, the situation written above is the example of subjective probability – each student has different subjective probability of receiving “A” grade.
According to Investopedia, “An example of subjective probability could be asking New York Yankees fans, before the baseball season starts, the chances of New York winning the world series. While there is no absolute mathematical proof behind the answer to the example, fans might still reply in actual percentage terms, such as the Yankees having a 25% chance of winning the world series.”
My own experience of using subjective probability in future might be, fro example, the derby event. I may think about the chances, which rider will win the derby and make a bet for this one.
Berger, James O. (1985). Statistical Decision Theory and Bayesian Analysis. Springer Series in Statistics (Second ed.). Springer-Verlag. ISBN 0-387-96098-8.
Bernardo, José M.; Smith, Adrian F. M. (1994). Bayesian Theory. Wiley. ISBN 0-471-49464-X.