Average days per application or Something else

[#1]

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

[jvitantonio]

Hi, you can try:

sum(Total NoOfApps)/sum(TOTAL DecisionDays)

JV

[#3]

try this:

=avg(aggr(DecisioningDays,NoofApps))

[jagan]

Hi,

Try like this

=Avg([Decisioning Days] * [No of Apps])

Regards,

Jagan.

[#5]

avg(aggr(DecisionDays,Application) where Application is your dimension so your are averaging the # of days by Application.  It is essentially summing the # of days per Application and dividing by the # of IDs (or Row Count).

[#6]

It's not the good method because most of the applications are decisioned between 0-2 days. Very few are decisioned in greater than 2 days but these greater than 2 days applications increase the average days per applications. e.g

Decisioning Days	%
0	1
1	7
2	6
3	2
24	1
25	1
30	1
Total Applications	19

[#7]

I see.  Due to your outliers, your averages will be skewed.  There are ways to remove outliers but the way I like to do it is to use a scatter chart in the same tab and allow the user to use the scatter chart to highlight the range without the outliers.  This way the user sees the outliers visually but can filter to only show averages without the outliers.  Not a perfect solution but great during data discovery phase

[#8]

Debbie,

You are right. These outliers skew the average. I need to show in a table. Any idea?

[#9]

this will give you the right avg:

=sum(DecisioningDays*NoofApps)/sum(NoofApps)

[#10]

It gives the same answer. Still not solved