I meant within the set of your 50 test scores, assuming they’re normalized to a common range.
To pick an extreme example: if all your test scores fall between 92% and 98%, it becomes less remarkable that your estimations of your test scores all fall within 3% of your actual test scores… anyone else could do about as well, given that fact about the data set. So it seems that knowing something about the distribution is helpful in reasoning about the causes of the differences in the accuracy of your judgments.
I meant within the set of your 50 test scores, assuming they’re normalized to a common range.
To pick an extreme example: if all your test scores fall between 92% and 98%, it becomes less remarkable that your estimations of your test scores all fall within 3% of your actual test scores… anyone else could do about as well, given that fact about the data set. So it seems that knowing something about the distribution is helpful in reasoning about the causes of the differences in the accuracy of your judgments.
Oh, that makes sense.
Nope, still a big difference. For example, here are my scores from the last few weeks:
Predicted/Actual: 98/100 72/72.5 94/94 85/86 82.5/87.5 90/92
Interesting that there were no too-high predictions.