The existence of factors which could adjust the score either up or down does not indicate which factors dominate. In this case, you have no information which suggests that 39700 is either above or below the median, and therefore these two cases must be assigned equal probability—canceling out any “regression to the mean” effects you could have predicted. Similar arguments apply to other effects which change the score.
So you estimate “regression to the mean” effects as zero, and base your estimate on any other effects you know about and how strong you think they are. That makes sense. Thanks for the correction!
In this case, you have no information which suggests that 39700 is either above or below the median, and therefore these two cases must be assigned equal probability
Not quite, you have some background information about the range of scores video games usually employ.
And, I suppose, information about the probability of people mentioning average scores. I concede that either factor could justify arguing that the score should decrease.
The existence of factors which could adjust the score either up or down does not indicate which factors dominate. In this case, you have no information which suggests that 39700 is either above or below the median, and therefore these two cases must be assigned equal probability—canceling out any “regression to the mean” effects you could have predicted. Similar arguments apply to other effects which change the score.
So you estimate “regression to the mean” effects as zero, and base your estimate on any other effects you know about and how strong you think they are. That makes sense. Thanks for the correction!
Not quite, you have some background information about the range of scores video games usually employ.
And, I suppose, information about the probability of people mentioning average scores. I concede that either factor could justify arguing that the score should decrease.