I think there is a really simple answer. I got a Table after using the Cross Validation Tool in ArcGIS. I dont know how you get the StdError, Stdd_Error and the NormValue. The StdError is the Standart Error of Prediction so i think its just SE = standard deviation / √n. I googled a lot and i have no idea. Can anybody help. Thx
FID | Measured | Predicted | Error | StdError | Stdd_Error | NormValue | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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StdError is the standard error of prediction. This is equal to the square root of the kriging variance, which is one of the outputs of the kriging equations.
Stdd_Error is the standardized error. This is equal to Error divided by StdError. Ideally, these values should follow a standard normal distribution.
NormValue is the equivalent quantile on the standard normal distribution for each standardized error. If you make a scatterplot of NormValue versus Stdd_Error, this is called Normal QQPlot, and it is useful for testing whether the standardized errors actually do follow a standard normal distribution. Ideally, the points should create a straight line at a 45 degree angle in the scatterplot.
Thx Eric Krause. Helped me a lot;)