I seek the wisdom of more statistically-minded monks.

I am writing a script in Perl which will tell me when a data feed has finished downloading the majority of its files based on a prediction of its total volume of files.

Example:
My calculated prediction (based on a neural network result): 1400 files
I have recv'd: 1389

Currently, I am simply checking to see if the recv'd amount is within 95% of the prediction. So for this example, this feed would be marked as "completed." The # of files recv'd for a feed this size might vary +-50 files and still be OK.

However, I have since added feeds that recv smaller amounts of data.

Example:
Prediction: 10
Recv'd: 8

Now, 8/10 is only 80%. However, this is probably OK as the feed just has fewer files.

What I'm wondering is this:

Is there a clever way to set some kind of tolerance range that I can use to check feed completion of all sizes against their predictions which will scale better than a percentage?

In reply to Calculating Completion of Feeds with Varying Volumes by temporal

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