Interesting question, wondered that myself as well. My statistics are a little rusty, so doing a quick simulation shows that the range is about .25-.29 (code sample 1). However, things like operations aren't completely random, and you might be more correct by looking at something like a Poisson process, resulting in a range of about .14-.44 for this sample size (code sample 2).
All in the end to be taken with a grain of salt of course, as the planning component of operations eliminates most statistical properties :)
All in the end to be taken with a grain of salt of course, as the planning component of operations eliminates most statistical properties :)
``` operations = np.random.randint(0, 365, 980000) pd.Series(operations).value_counts().sort_values() / 980000 ```
``` x = np.random.poisson(.0089, 1000000) x = (pd.Series(x).cumsum() / 24).round() x.groupby(x).count().iloc[:365].sort_values() / 980000 ```