ok sorry for not being clear. I have two sets of data. One column contains Observed or experimental focal length of a lens at different heights from the axis. The Other column contains the expected or theoretical value of focal length. so yeah I want to quantitatively know different these two sets of data are given the uncertainty and errors in the observed dataDale said:The standard measure of distance would be the sum of square residuals. However, I am not sure what you are asking has real meaning as stated.
As I understand your statement, you don’t have two sets of data, you have one set of data and a model. Any set of data can plausibly come from any model given sufficiently uncertain measurements. So just asking about the sum of square residuals doesn’t say much.
If your model has any free parameters then you can meaningfully ask which parameters minimize the residuals. Or if you have two competing models you can ask which model minimizes the residuals. Or if you can predict the expected uncertainty in your measurements, then you can determine how likely the data is under the model.
Does this column have uncertainty associated with it?VVS2000 said:The Other column contains the expected or theoretical value of focal length
yes, but all values have the same uncertaintyDale said:Does this column have uncertainty associated with it?
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