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Year | Question_Number | IC | Organization | Positive |
2019 | 1 | Agency | Agency | 85 |
2019 | 2 | Agency | Org1 | 96 |
2020 | 1 | Agency | Org2 | 88 |
2020 | 2 | Agency | Org3 | 95 |
2021 | 1 | Agency | Org4 | 90 |
2021 | 1 | Agency | Org5 | 83 |
I would like to calculate the chi square p-value between the avarage agency positive rating and a specific organization (e.x. org1) for year 2020. I have question number as a filter.
The table above shows structure of my data.
I have my DAX code that I wrote below, but the p value it is giving me is not correct. I used the same data and conducted a chi square test and it renders different p-value- please advise.
Significance vs Agency =
var _year = 2020
var _question_no = SELECTEDVALUE(Sheet1[Question_Number])
var _actual = CALCULATE(AVERAGE(Sheet1[Positive]),Sheet1[Year] =_year)
var _expected = CALCULATE(AVERAGE(Sheet1[Positive]),
FILTER(ALL(Sheet1),
Sheet1[Year]=_year && Sheet1[IC]="Agency"
&& Sheet1[Organization]="Agency"
&& Sheet1[Question_Number]=_question_no
))
VAR ChiStat = ((_actual-_expected)^2)/_expected
--VAR DegreesFreedom = (COUNT(Sheet1[Positive])-1)
RETURN
CHISQ.DIST.RT(ChiStat,5)
A chi2 test can test 2 things:
1) distribution goodness-of-fit and
2) whether 2 categorical variables are independent.
What are you trying to achieve here? I can't see any relevance of what you're doing to the above.
Here's an excerpt from When to Use a Chi-Square Test (With Examples) - Statology:
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