Dancing David
Penultimate Amazing
Thanks for all of the information. It will take me a while to read and digest. Preliminarily, however, if Radin has selectively cited 3145 favourable ganzfeld experiments out of a little under 7,000, that still would mean that the overall hit rate would be highly statistically significant, if Radin is correct that 1008 of the 3145 experiments that he cites produced hits. For example, assume that there actually are an additional 4000 experiments that overall produced chance results of 25% hits, or 1000 hits total. That would bring the total number of ganzfeld experiments to well over 7000 (7145). The total number of hits would be 2008 (the 1008 cited by Radin plus the assumed additional 1000). That would produce an overall hit rate of 2008 out of 7145, or 28.1%. While, to the layman, that might seem only narrowly above the chance rate of 25%, with that many experiments the true odds against chance would actually be 986 million to 1. In fact, using an on-line binomial calculator, if you put in 7145 for the value of "n", 2008 for the value of "k", and 0.25 for the value of "q" and click on calculate, you will obtain a "P" value for "2008 or more out of 7145" so small that it is not even calculated exactly, but simply shows as "<0.000001." See http://faculty.vassar.edu/lowry/binomialX.html
So, to invalidate the ganzfeld experiments, it appears that something more than selective inclusion must be found.
The statistics would be nicer if there were better controls in place.
1. Each picture needs to have matching words that are assigned to it, this is a crucial control, otherwise the probability of a match is not twenty five percent. It is unknown.
2. Then the word distribution associated with each picture needs to be examined, at what rate do certain picture match certain words.
3.Then each set of pictures can be controlled for a very impotant variable called by me 'the random match rate'. each set should contain pictures that match different words. So no two pictures should be adjudged as having the same matching words. This has to be done, becuase fior the probability of a word match to be twenty five percent you have to do this.
4. then the overall distribution of words given by the reciever must be examined and the target pictures have to be matched against this random, or pseudo random match rate of just random words stated by the reciever. this would eliminate then the probabilty of a picture having a fifty per cent match to any random word selection.
These are the controls that need to be in place. Otherwise the 'target' picture might have a rate of 50% random match to any given reciever string, that would then raise the probability above 25%. especialy if all the pictures in a set have high match rates to random reciever strings.
For the ganfeld to be significant you have to prove that the given match rate is 25%, you can't assume that the given match rate to a randomly chosen reciever string is 25%. ceratin pictures could have a much higher or lower match rate to any given set of reciever word strings.
That is why the ganzfeld data is not valid at this point.