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Hi,
I have the following data. I want to calculate average decisioning days per application. I think average would not be the better to calculate it. Which one would be better method to calculate.
ID | Decisioning Days |
11111 | 0 |
11112 | 1 |
11113 | 2 |
11114 | 1 |
11115 | 2 |
11116 | 2 |
11117 | 2 |
11118 | 1 |
11119 | 2 |
11120 | 1 |
11121 | 1 |
11122 | 3 |
11123 | 3 |
11124 | 1 |
11125 | 1 |
11126 | 2 |
11127 | 30 |
11128 | 25 |
11129 | 24 |
Why don't you try
median(aggr(DecisionDays,Application)
Another option to consider
from QlikView Help:
mode([{set_expression}][ distinct ] expression)
Returns the mode value, i.e. the most commonly occurring value, of expression or field iterated over the chart dimension(s). If more than one value is equally commonly occurring, NULL is returned. Mode can return numeric values as well as text values.
Mode does not support the total qualifier.
Examples:
mode( Product )
mode( X*Y/3 )
how should I write expression for my data?
If you are familiar with standard deviation you can use that to exclude
this values that are outside of the acceptable range but I would put a
toggle to allow the user to turn the exclusion off and on and allow them to
drill into the data to see the outliers. Never good to exclude data. You
want to investigate the cause of these outliers whether bad data or not.
Then how should I do with this data?
sorry for lack of responding. I have been tied up with a client. Let me look back to an application I created years ago using the standard deviation calculation as a filter to highlight and include/exclude outliers. From what I recall it worked for what the business wanted.
Hi Debbie,
Apologies, I was out of office. Did you get any chance to have a look on it.