Cross Validation/calculate StdError, Stdd_Error, NormValue

Question

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

01234567891011121314151617181920

470,073195912,403881453,583461483,765499541,13589766,325671288,17376904,216706659,680241676,788004666,22003480,821565287,342394123,791379938,267365938,267365646,036572443,2775221087,176937827,379415778,769581

779,4643553482,4430333631,5594783439,5693293574,8925245885,4098264508,1779974719,7978101689,80433679,3637665637,4872852413,8124286577,9679624658,5721968936,7664019919,780191354,8780993675,5704577731,8108183949,9845209852,6773521

309,3911603-429,9608477177,9760173-44,1961697533,75663448119,0841554220,0042374-184,418895930,124088982,575762471-28,73274476-67,00913635290,6255684534,7808178-1,500963141-18,48717397-291,1584727232,2929357-355,3661187122,605105973,90777111

197,9004352187,2076829222,1929554222,8177887225,6868838217,4111495204,8373173157,9156231170,0014572192,6182741189,5340294211,093082268,3646909184,683788965,6312421366,37976517206,0541435225,8855784198,56918194,0884513205,7042675

1,563367761-2,2967051410,80099757-0,1983511730,1495728680,5477371131,074043735-1,167831860,1771990050,013372368-0,15159676-0,3174388081,0829500982,895656522-0,022869644-0,278506167-1,4130192571,0283655-1,7896338130,631697070,359291385

1,465233798-1,980752410,637484163-0,49720058300,3661063710,967421551-0,9674215510,119648099-0,119648099-0,366106371-0,7916385981,1797611081,98075241-0,241040395-0,637484163-1,1797611080,791638598-1,4652337980,4972005830,241040395

MarcGoetzke · Answer

Thx Eric Krause. Helped me a lot;)

Eric6346 · Answer

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.