Hello,
I have a data set containing all response ever recorded for several different surveys.
I would like to build a dashboard that allows the user to select a question and see the response rates for that question (accomplished this by creating a variable and using case statements).
The backend > grouped rows by survey to get a count of participants per survey > divided number of responses (case statement variable) by total count of participants per survey. (Tested with only 3 survey questions shown below).
The result in a table format is that I can see the survey and response rate for what ever question selected.
Now, I'd like to filter out surveys where the response rate for that question was less than 15% and get the final average for that.
When in table format, this isn't an issue and surveys with less than 15% response rate for that question are removed.
However, for the gauge, the filter doesn't seem to apply well to the data.
I'm wondering why this is happening and why the max is only .05?
I think it has something to do with the math on the backend. The average (after all response rates <.15 should be around 37.8%β¦.
The gauge average without filtering is correct for the selected question (0.14%).