Quote:
Originally Posted by Revsmile
Robert,If we form the first group of 345 observations, each one separated by 29 days, and then form the second group in the same way, everyone of the daily observations in the second group will be consecutive with an observation in the first group. Will then the grouped data variates 1 and 2 be independent? Will they be normal? I realize that I am questioning now my earlier claim that they were normal, but with this correlation amongst the data in different groups, the speed of convergence to the normal could be an issue. We also know that the original data is highly skewed, probably non-stationary and autocorrelated. How good will the normal distribution and the assumption of independence be? You seem to be using the same data for different planet-moon angles. Why are these different analyses independent? The groups would be related to each other, wouldn't they? If this is the case, you cannot keep searching thru the results, and when an unusual value pops up, claim to have an accurate significance level for it. Also, if you are going to use mathematical terms such as "random walk", define it please, or use an accepted definition. I don't think a random walk is a good model for the daily data. In a random walk, the variance of each daily variate grows without bound. Finally, is it your hypothesis that there is a 29 day cycle in the data? Is that it? If so, why look at any other moon-planet groupings? Why not just look at the correlation with the moon ?
Peter
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This is helpful, but does not affect the problem at hand. The point is that the data may be dependent (ie the result for one of the 29 groups may relate to the result for the previous and subsequent groups), but this is irrelevant to the existence of large spikes in the data. For example, plugging the 29 data groups listed at
Planets and Rain para 5 into a chart will show two non-random features – (i) a tendency for most points to be closer than average to the preceding point, and (ii) two big spikes. Feature (i) is caused by autocorrelation, while it appears that (ii) can only be caused (subject to verification) by the planetary effect.
The reason the different planetary analyses are independent is that the positions of the planets are independent – hence there is very little overlap in the data points producing the different significant results. Thank you for the clarification on use of random walk, I was familiar with its use in the context of Nile River height analysis and had not understood it necessarily involved boundless growth.
My hypothesis is not just a 29 day cycle but a planetary effect, with the base point of the lunar cycles shifting with each planet. I have already referred at
Planets and Rain to the sun-moon cycle with its highly significant anomaly in rain level at the first quarter. I have now done an additional analysis using just the position of the moon against the zodiac, and while the variance appears to be less, with only two points close to standard deviation = 2, the autocorrelation was much stronger, with high and low rain during several common three day periods.
The 29 data points for the lunar zodiac cycle are: 1308.6;1517;1201.4;1141.2;1332;992.6;1035.8;1091.8 ;1232.6;1397.8;1240.2;908.4;911;948.6;1157.1;1520. 8;1389.4;974.8;1328;1179;957.8;1327;1078.6;859.1;9 07.8;935.5;1185.4;1045.6;1027.8;
And for the sun moon cycle:
1280.4;1285;1288.2;873.8;850;1096.8;969.8;1541;162 0.8;1233.4;905.4;977.8;1258;1093.8;1223.4;975.6;86 5;1293;1066.8;1257.6;922.6;1200.7;1188.4;925.8;103 4.4;1120.8;1047.5;1326.6;1410.3;