>>Say I have a set of data that is the price of a home.
>>
>>100,000
>>125,000
>>92,000
>>175,000
>>135,000
>>10,000
>>500,000
>>
>>Well, I know that the 10,000 fiqure is really just for a lot. So when figuring trends, I need to throw it out. I also know that the 500,000 fiqure is also way off, so it too needs to be thrown out.
>>
>>If each of these numbers were in a field in a dbf(one per record) How could I programmatically throw out numbers that were way off? I have tried diffrent forms of average and standard deviation, but nothing seems quite right. I need some high school algebra or statistics lessons I think.
>
>Well, some things you are leaving out. Will there always be a low and high which will need to be dropped out? Can you setup a simple range to compare values record to record. Setup an index on value and determine the difference between the numbers to establish a reasonable range. If a number falls way-out of the range then drop it. Is there another field that can be used to identify stuff to exclude. How do you know that $10,000 is a lot value? htwh


Yes, most of the time there would be a high and low, but sometimes just one or the other. I know that the low number is a bad price logically. If all homes next door to one another are selling for x average, then one that is 10,000 is way below. No, there is not another field I can use.

My basic question is, what is an exceptable range to include statistically? the middle 80%, the middle 40%, etc.