Correlation test for model outputs

[Richard_R]

Hello all,

I am currently building a model in Excel for predicting domestic water demand on a daily basis. The daily model will be compared to a more accurate model which runs on timesteps of 5 minutes (the latter is data intensive however which is why we are building a daily model as it requires less data).

Does anyone know what the correct correlation/statistical approach is to compare the daily model results with the 5 minute model? I have aggregated the results from the 5 minute model to a daily timestep so results can be directly compared, i.e.

http://sudsolutions.co.uk/misc/model_results.PNG

Excel has CORRELATION and PEARSON statistical functions so was wondering if I need to use one of these. The results aren't in the form of y=mx+c so I don't think I want an r^2 "goodness of fit" test (or do I?).

Thanks in advance for any help.

Regards
Rob

 

[ych22]

PEARSON or CORRELATION seem to be the way to go for your data (from excel help I think they do the same thing?)

Correlation can broadly refer to either linear or nonlinear correlation. I suppose you are interested in the linear case, and thus can use a linear regression model in the form of y = mx + c to analyze the data.