从Power BI中的值和频率列计算标准偏差 [英] Calculating the standard deviation from columns of values and frequencies in Power BI

问题描述

我试图在PowerBI中计算一组值的标准偏差，但我遇到了麻烦。表格中有两列（天数和计数）。这是运输车道的频率分布。天数从1到100，计数是花费这些天数的发货数。

用于计算频率分布的标准偏差的公式非常简单：sqrt（sum（fx *（x-avgx）^ 2））/ sum（fx ））但是达克斯让我头疼不已。任何帮助将非常感激。谢谢。

解决方案

我从

转换为Power BI等效项并满足您的天数要求：

然后按如下所示创建度量，棘手的部分是利用

PS Power BI实际上具有一些用于计算标准偏差的内置功能，例如 STDEVX.P ，但是在这种情况下，它没有那么有用。随时检查一下。

I am trying to calculate the standard deviation of a set of values in PowerBI and I am stuck. There are two columns in a table (days and count). This is a frequency distribution of a transportation lane. Days goes from 1 to 100, count is the number of shipments that took those number of days.

The formula to calculate the standard deviation of a frequency distribution is pretty straight forward: sqrt(sum(fx * (x - avgx)^2))/sum(fx)) But the Dax is giving me a massive headache. Any help would be much appreciated. Thanks.

解决方案

I took the example from the Standard deviation Wikipedia page as sample data.

Converted to Power BI equivalent and fit your requirement as days and count:

And the measure is created as follows, the tricky part is to make use of the SUMX function. I deliberately break down the intermediate steps with VAR to make it more clear.

st_dev = 
VAR x_sum = SUMX(Lane, Lane[Days] * Lane[Count])
VAR x_count = SUM(Lane[Count])
VAR mean = x_sum / x_count
VAR dev_sq_sum = SUMX(Lane, POWER(Lane[Days] - mean, 2) * Lane[Count])
RETURN SQRT(dev_sq_sum / x_count)

Result:

P.S. Power BI actually has some built-in functions for calculating standard deviation, e.g. STDEVX.P, but it's not that useful in this case. Feel free to check it out though.

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