As soon as I posted that, I knew that it was fundamentally flawed. A more honest way to do the calculation would be to take those two high scoring affairs and instead of zeroing them out, assigned the average runs per game to those two games and total that up. But then you would have to do that to all teams. Too much work.
I thought that it was that if you arranged the scores highest to lowest, the median would be where 50% of the scores were on the left and 50% of the scores were on the right. What I don’t understand is the value of calculating the median over the value of calculating the average. I don’t doubt that there is some, but I have no clue what it is.
A key advantage of the median is that it is less sensitive to outliers or skewed data. For example, in a dataset with extreme values, the median provides a more representative “typical” value than the average, which can be heavily influenced by these outliers. This makes the median particularly useful when dealing with skewed distributions, such as income levels or house prices, where a few very high values can distort the average
I can, too, and that is directly attributable to Ms Quaite, my 11th grade English teacher. Happily, she spoke in a high pitched, singsong manner, and she was (still is, as far as I know) a native Texan, so in my head I always hear it recited by a sort of redneck Julia Child. I wouldn’t have it any other way.
The Brewers did an alumni HR derby after yesterday’s game for their stadium’s 25th anniversary. Sounds like it would have been a lot of fun if it wasn’t full of players I fucking hate. I would pay good money to attend the Astros version. Not sure how well Bags and Bidge can still swing it, but I’m sure Thunderpants could knock a couple.