Hi Chris,
If I understand your question correctly, what you want is both easy and hard.
Easy:
# making a reproducible example, as asked in the posting guide
# two vectors
water <- rnorm(1000)
rain <- rgamma(1000,.5)
# the following does everything you mention and more
summary(lm(water~rain))
cor(water,rain)
Hard:
lm() and cor() assume independence of observations, linearity of the relation, normality of the
residuals. Are these assumptions valid for your problem?
Are your datasets time series? There will be ??autocorrelation in both datasets. There may be a
?lag. Decide whether to estimate and correct for those.
Are there multiple sample locations? There may be dependence.
Would you rather assume rain and change in groundwater level are related?
Etc.
Cheers,
Arien
Chris Li wrote:
Hi all,
I have got two datasets, one of them is rainfall data and the other one is
groundwater level data.
I would like to see whether there is a correlation between these two
datasets and if there is, to what extent they are correlated.
My stats background is limited, therefore any advice on which command I
should use in R would be greatly appreciated.
Thanks in advance.
Chris
--
drs. H.A. (Arien) Lam (Ph.D. student)
Department of Physical Geography
Faculty of Geosciences
Utrecht University, The Netherlands
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