Join us at FabCon Atlanta from March 16 - 20, 2026, for the ultimate Fabric, Power BI, AI and SQL community-led event. Save $200 with code FABCOMM.
Register now!Vote for your favorite vizzies from the Power BI Dataviz World Championship submissions. Vote now!
I am trying to calculate the correlation coefficient using a quick measure. However I am kind of puzzled by the fields is requires.
I come from a R background and here we only send in 2 column to calculate the pearson coefficient. However the quick measure asks me for a third one, the category.
What is this category?
Solved! Go to Solution.
@Anonymous
You can use the Quick Measure after adding an Index column to your dataset if you do not have a column with unique values. This is required by the Quick Measure to calculate the correlation coefficient over a category.
If you really need to calculate with only two columns then find below the modified measure. I have also attached the PBIX file. Do verify the result from your model.
Age and Gluco correlation =
VAR __CORRELATION_TABLE = 'Table'
VAR __COUNT =
COUNTX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) * SUM('Table'[Gluco]))
)
VAR __SUM_X = SUMX(KEEPFILTERS(__CORRELATION_TABLE), CALCULATE(SUM('Table'[Age])))
VAR __SUM_Y = SUMX(KEEPFILTERS(__CORRELATION_TABLE), CALCULATE(SUM('Table'[Gluco])))
VAR __SUM_XY =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) * SUM('Table'[Gluco]) * 1.)
)
VAR __SUM_X2 =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) ^ 2)
)
VAR __SUM_Y2 =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Gluco]) ^ 2)
)
RETURN
DIVIDE(
__COUNT * __SUM_XY - __SUM_X * __SUM_Y * 1.,
SQRT(
(__COUNT * __SUM_X2 - __SUM_X ^ 2)
* (__COUNT * __SUM_Y2 - __SUM_Y ^ 2)
)
)
⭕ Subscribe and learn Power BI from these videos
⚪ Website ⚪ LinkedIn ⚪ PBI User Group
Hi all, I have used the quick measure to calculate the correltion (r value), however, it has returned a value greater then 1. Has anyone come acorss this error in their calculations? Obviously they must be an error as an R vlaue can only be between -1 and 1.
Thanks
Rich
@Anonymous
You can use the Quick Measure after adding an Index column to your dataset if you do not have a column with unique values. This is required by the Quick Measure to calculate the correlation coefficient over a category.
If you really need to calculate with only two columns then find below the modified measure. I have also attached the PBIX file. Do verify the result from your model.
Age and Gluco correlation =
VAR __CORRELATION_TABLE = 'Table'
VAR __COUNT =
COUNTX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) * SUM('Table'[Gluco]))
)
VAR __SUM_X = SUMX(KEEPFILTERS(__CORRELATION_TABLE), CALCULATE(SUM('Table'[Age])))
VAR __SUM_Y = SUMX(KEEPFILTERS(__CORRELATION_TABLE), CALCULATE(SUM('Table'[Gluco])))
VAR __SUM_XY =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) * SUM('Table'[Gluco]) * 1.)
)
VAR __SUM_X2 =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Age]) ^ 2)
)
VAR __SUM_Y2 =
SUMX(
KEEPFILTERS(__CORRELATION_TABLE),
CALCULATE(SUM('Table'[Gluco]) ^ 2)
)
RETURN
DIVIDE(
__COUNT * __SUM_XY - __SUM_X * __SUM_Y * 1.,
SQRT(
(__COUNT * __SUM_X2 - __SUM_X ^ 2)
* (__COUNT * __SUM_Y2 - __SUM_Y ^ 2)
)
)
⭕ Subscribe and learn Power BI from these videos
⚪ Website ⚪ LinkedIn ⚪ PBI User Group
Hi @Anonymous ,
You can check this explanation here:
https://community.powerbi.com/t5/Quick-Measures-Gallery/Correlation-coefficient/td-p/196274
https://xxlbi.com/blog/pearson-correlation-coefficient-in-dax/
Thanks,
Pragati
People asing the same question there do not seem to be getting a concrete answer.
Vote for your favorite vizzies from the Power BI World Championship submissions!
If you love stickers, then you will definitely want to check out our Community Sticker Challenge!
Check out the January 2026 Power BI update to learn about new features.
| User | Count |
|---|---|
| 64 | |
| 50 | |
| 42 | |
| 23 | |
| 20 |
| User | Count |
|---|---|
| 139 | |
| 116 | |
| 53 | |
| 37 | |
| 31 |