当进行此类评估工作时,请不要假定每天的消息都是平均分布的。
When doing these estimates, do not assume an even distribution of messages throughout the day.
示例的雇员总数约 100 人,他们平均分布在这两个地理位置上。
The sample population amounted to about 100 or so employees, evenly split between the two geographies.
假设对两个map的请求是平均分布的,那么这种技术在这种情况下将把可能的争用数目减半。
Assuming that requests against the two maps are evenly distributed, in this case this technique would cut the number of potential contentions in half.
And then I could also do a Gaussian one here, with the mean of and the standard deviation of volatility divided by 2.
然后我在这里再写一个高斯分布的函数,它的浮动值的平均值和,标准偏差值都除了2。
It could be normal, everything, that would be a Gaussian, where if you recall there was a mean, and a standard deviation, and most values were going to be close to the mean.
可能是正态分布,也就是高斯分布,只要有平均值和标准偏差值,你就可以进行调用,大部分的值都是集中在平均值附近的。
We've got kind of an even split there, pretty much an even split.
看来大家的意见分布得比较平均
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