Hi everyone,

I've been reading some of the replies to R Tulip's claims, but not all of them, so humble apologies as appropriate. I have to agree that the statistics used by Robert have not and could result in fruitful results. I do think it's worth saying (as I know him as my friend) he does adhere generally to scholarly methodology.

Looking at the statistics side of things there are one or two points worth mentioning (if not already)

The original question addressed I believe was whether the daily data correlates with a cyclical phenomena of period 29? And could the identification of this correlation be amenable via statistics ?

First, I understand that Robert has grouped the daily observation R( i ) with observation R (i+29m), for m=1,2 3 ... thus forming 29 groups.

If the above is correct, then adding the rainfalls in each group, could, because of the central limit theorem result in approximately normal variates. If the original daily data are variates with finite means and standard deviation then the normal distribution should be assumed. However there are only 29 of them, so the statistical power will not be very good.

A better way (if one believed that an explanation could ever likely to be consistent with science) is to model the daily data with terms such as Day effect, (1-29), as well as regressive terms and non-normal error terms.

has not found convincing evidence of a 29 cycle - and his statistical techniques should be tightened up significantly. Also, correlation is not causation (as Robert has earlier implied). This error must wait until after good statistical tests have been made.