I have been tasked with analyzing the input flow in a water tank in relation to a number of weather parameters. In a narrower sense, I have to investigate any possible effect that these variables might have on the variable of interest.
That being said, I don't know which method(s) to apply as I'm thinking only of Pearson's correlation coefficient. Even with this one, the sampling rate is different as the weather conditions are measured every 3 hours while input flow every 5 minutes. Should I average over 3 hours, disregard data not corresponding to weather dataset timestamp or would you suggest something else?weather = [ (1.21,0) , (1.08, 0.5), (1.04, 1), (1.02, 1.5)]input_flow = [ (120,0), (124,1)]
A representation of such data where the first index is the value of the parameter while the second one is time in seconds
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