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Hello,
I am trying to calculate standard deviation from my data:
| Product | Profit | Count | Total |
| 1 | 100 | 5 | 500 |
| 1 | 200 | 4 | 800 |
| 1 | 300 | 3 | 900 |
| 1 | 400 | 1 | 400 |
| 2 | 100 | 7 | 700 |
| 2 | 200 | 3 | 600 |
Total = Profit * Count. I am trying to calculate the standard deviation per product using the Total column as the value and the Count column as the counts. I was able to create a calculated column for mean:
Mean = CALCULATE(SUM(total) / SUM(count), ALLEXCEPT(table, product))
The DAX for STDEV doesn't seem to work for me as I was getting an extemely large number. Please help me find the correct way to calculate the standard deviation.
Thanks in advance!
Solved! Go to Solution.
Well, I think I figured it out. Here's the solution:
@kirbynguyen What number are you expecting? The default Standard Deviation aggregation seems correct to me.
I've calculated the Standard Deviations by hand and I got 96.0769 for product 1 and 45.8258 for product 2.
But this is the result when I used the STDEV functions:
This is because it doesn't take into account the total counts and I couldn't figure out a way to include it.
@kirbynguyencan you show the formula that you used to arrive on 96.0769 for product 1 and 45.8258 for product 2
Okay, I didn't do it by hand, but I plugged the numbers into a calculator 😛
@kirbynguyen DAX is working as expected
once your dataset is like this
Well, the dataset was just a sample. I don't want to pivot my data since the counts are very high and there are more filters than just "product". Thanks for the input though!
Well, I think I figured it out. Here's the solution:
@kirbynguyen were you hoping for this
_total:= CALCULATE(SUMX('Table 1','Table 1'[Total]),ALLEXCEPT('Table 1','Table 1'[Product]))
_count:= CALCULATE(SUMX('Table 1','Table 1'[Count]),ALLEXCEPT('Table 1','Table 1'[Product]))
_mean:= DIVIDE([_total],[_count])
_sq:= (MAX('Table 1'[Total])-[_mean])^2
_sumsq:= CALCULATE(SUMX('Table 1',[_sq]),ALLEXCEPT('Table 1','Table 1'[Product]))
STDEV:= SQRT(DIVIDE([_sumsq],[_count]))Vote for your favorite vizzies from the Power BI World Championship submissions!
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