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!To celebrate FabCon Vienna, we are offering 50% off select exams. Ends October 3rd. Request your discount now.
i am in a very peculiar requirement of calculating cp cpk in powerbi using the formula for sigma estimator as "sbar/c4" check reference link here
My sample data is as given below
06-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.31 | 18.2 | 18.8 |
09-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.428 | 18.2 | 18.8 |
16-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.364 | 18.2 | 18.8 |
19-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.48 | 18.2 | 18.8 |
22-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.49 | 18.2 | 18.8 |
28-10-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.407 | 18.2 | 18.8 |
01-11-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.512 | 18.2 | 18.8 |
17-11-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.506 | 18.2 | 18.8 |
19-11-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.472 | 18.2 | 18.8 |
21-11-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.507 | 18.2 | 18.8 |
22-11-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.596 | 18.2 | 18.8 |
19-12-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.517 | 18.2 | 18.8 |
21-12-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.529 | 18.2 | 18.8 |
22-12-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.481 | 18.2 | 18.8 |
23-12-2019 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.634 | 18.2 | 18.8 |
01-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.451 | 18.2 | 18.8 |
02-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.375 | 18.2 | 18.8 |
03-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.403 | 18.2 | 18.8 |
06-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.404 | 18.2 | 18.8 |
07-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.54 | 18.2 | 18.8 |
10-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.614 | 18.2 | 18.8 |
12-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.668 | 18.2 | 18.8 |
13-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.548 | 18.2 | 18.8 |
16-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.497 | 18.2 | 18.8 |
25-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.577 | 18.2 | 18.8 |
26-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.517 | 18.2 | 18.8 |
28-01-2020 | Dummy | Gaon | 37 | Cap191002 | 1 | 10 | READING7 | 18.481 | 18.2 | 18.8 |
09-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.499 | 18.2 | 18.8 |
15-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.429 | 18.2 | 18.8 |
17-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.347 | 18.2 | 18.8 |
17-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.59 | 18.2 | 18.8 |
19-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.433 | 18.2 | 18.8 |
22-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.478 | 18.2 | 18.8 |
26-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.569 | 18.2 | 18.8 |
29-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.701 | 18.2 | 18.8 |
29-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.496 | 18.2 | 18.8 |
30-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.548 | 18.2 | 18.8 |
31-03-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.604 | 18.2 | 18.8 |
01-04-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.558 | 18.2 | 18.8 |
02-04-2020 | Dummy | Gaon | 37 | Cap200303 | 1 | 10 | READING7 | 18.63 | 18.2 | 18.8 |
here we need to calculate cp cpk for the city label column as a subgroup,... this is a sample but in reality, there would be 1000s of city labels, 10 different country names, 40 state names. PO box no, Readings and Box size is to be ignored
C4 value is decided to be 0.9727 as subgroups are considered to be 10
I want to know how do I create a DAX query to calculate the new sigma value
my current query is like this
Cpk = VAR sigma = STDEV.S(Table[Value]) VAR estimatedMean = AVERAGE(Table[Value]) VAR Cplower = (estimatedMean-MIN(Table[LSL Value]))/(3*sigma) VAR Cpupper = (MAX(Table[USL Value])-estimatedMean)/(3*sigma) RETURN MIN(Cplower,Cpupper)
the new query can dynamically change as per slicers selected in Powerbi eg country, state type, state name, etc
Please help me out, the condition is very critical
Hi @Anonymous,
The column headers you provide cant match the data below,pls check wheher the headers should be as below:
What is your expected output?If possible,could you pls upload your sample .pbix file?
Best Regards,
Kelly
Did I answer your question? Mark my post as a solution!
User | Count |
---|---|
98 | |
75 | |
69 | |
49 | |
26 |