IUofC: “It appears that the website simply quotes the PEAR data as-is. The core of the rebuttal on PEAR's research is that the change is very small, and only discernible due to the uniquely large sampling rate. Some would say 'thats good science' - a large sampling rate. Others like the author of this article would say 'stretching the trials out to such number so that a tiny variation becomes more apparent, when under normal size sampling groups wed see no difference', believe its bad science. I think this is the core issue.”
Tom: The changes are small but that does not mean they are statistically insignificant. An electron is small (and significant) yet it is only discernible due to extremely precise measurements. An extremely precise measurement of small changes in a statistical distribution requires a very large sample sizes. Consequently, if sample sizes are large enough, a small change in a statistical distribution can be measured so accurately that the probability that the change is real and significant can be huge. As I recall, the statistics of many of the PEAR experiments are exceptionally statistically significant (like 1 to 36,000 that the results could have been randomly generated (were just luck or due to error). Here is a made up example to illustrate the idea of “small but significant”: if objective causality predicts that a given result must be exactly 100, and PEAR Labs gets a measured result of 102.253694675 with experimental error bars of plus or minus 0.000000002 . [Here, the error bars represent ALL potential sources of possible error]. This resulting difference is small but the statistical significance is huge. The math says that the odds are much greater than a million to one that objective causality is in error. Because the PEAR measurement was so precise, this small difference provides solid scientific evidence that objective causality makes an incorrect prediction. (typically 1,000 to one is considered very strong scientific evidence)
Princeton (where Einstein and Bohm worked) was, and is, a very strong science institution. The people involved in PEAR experiments use immaculate scientific protocols. Because they get results that fly in the face of scientific belief, the quality of their science is no doubt much better and stringent than typical scientific research. Why all the wondering about the quality of PEAR lab's work? Simply go to PEAR labs web site and study their research -- they have it all laid out there. http://www.princeton.edu/~pear/
Look at the experiments, read about the protocols, see the results. I have. But for a short summary, listen to the new 15 minute video summary on the upper right-hand corner of their home page. There you will find out that the statistical significance of the ensemble of all their experiments is about one trillion to 1 that the effects are real and not experimental error or equipment noise or any other error source. I doubt that there are many (probably none) single subject experiments in any field that have results that are so clearly and decisively proven as these. [In these types of experiments, the evidence that the effect you have seen is real is measured in terms of its statistical significance]. Mathematics concludes that the odds are a trillion to one that PEAR Labs has indeed proven that mental intention affects physical process. To assess the quality of their work, one only has to read their research reports – the video mentioned above provides much insight into their approach.
You ask what do I think about this criticism of PEAR labs credibility and how would I respond to it? Here it is: The critics are in denial -- true believers in an objective causal reality and do not deserve to call themselves scientists. They are instead the high priests of an objective reality belief system. Their criticism is profoundly inane, misinformed, and factually wrong. Under statistical conditions such as these (multiple repetitions), it is a fundamental mathematical fact that Larger sample size must produce better, more accurate, statistics. Statistical significance is a simple objective calculation – and PEAR Labs has done it properly with data collected under immaculate scientific protocol. There need not be any question about this issue -- the data and research is all there, all any real scientist has to do is look at it with open-minded skepticism. At PEAR labs, the scientific rigor and statistical significance is far above and beyond what is deemed reasonably rigorous and significant for most scientific research.
One can never change a true believer's mind with a rational argument or with scientific evidence because belief is not rational. The people who say "why don't you just prove what you say is true with a demonstration and everyone then would know it is true and accept it -- you would change science over night if the proof
were irrefutable" are very naive and don't understand how our culture or our science works. Speaking about naïve, this line of reasoning is always good for a laugh: “If PEAR labs has done all that, why haven’t they collected the “Randy prize” for scientifically proving that the paranormal exists?” The randy Prize is not a genuine offer; it is what is commonly called a publicity stunt or a propaganda campaign -- a sham to discredit the infidels and attract and trap more believers. With PEAR labs, we have not just an individual on the fringe but a Princeton University team of scientists with tons of irrefutable evidence and they can't get it published in the standard journals. Critics blow off uninformed hot air, and are taken seriously. Point made. Rational scientific evidence does not trump cultural and scientific belief no matter how irrefutable the evidence is.
And, worst of all: Most of the people who read this will find it very difficult to believe that what I just said is the plain and simple truth. "There must be more to it than that" they will think, "PEAR lab's evidence couldn't be that irrefutable and the large number critics who are professional scientists couldn't ALL be that incompetent and caught like mindless rats in a belief trap -- something just doesn’t add up here".
The People in charge control the PR (propaganda) machine and the people without direct first hand knowledge are gullible. So it has always been in most cultures.