(2018-05-30, 09:28 AM)Typoz Wrote: Dean Radin interview on Waking Cosmos.
http://www.originsofconsciousness.com/or...ic-science
Also available as MP3 download.
Towards the end Radin talks about a new device consisting of 32 channels of "quantum noise", in which, rather than the approach used in previous micro-PK work and the Global Consciousness Project, the raw noise is recorded rather than being transformed into a stream of bits. This allows the calculation of autocorrelations for each channel (correlations based on different points in time) and mutual information (correlations between the different channels). The records apparently showed anomalous behaviour at around the time when the result of the 2016 US presidential election was announced.
There's more about this in another interview with Radin on a blog called alpha411 (at about 36 minutes):
http://alpha411.blogspot.com/2018/04/par...erica.html
Radin explains that the motivation behind recording the raw noise (every millisecond), rather than a bitstream derived from it, is to avoid applying XOR processing. XOR processing eliminates any bias in the raw signal, and therefore throws away any effect on the relative proportions of 0s and 1s in the bitstream, making it difficult to work out what is causing any anomalous behaviour that's observed. Radin says here that the p values obtained from the presidential election were stupendous - equating to odds of 226 million to 1 for autocorrelation and 81 thousand to one for mutual information.
Of course, taken at face value, this would represent some of the strongest evidence for an anomalous effect ever obtained. For example, it would be far more significant than single events in the Global Consciousness Project. However, it's not clear from these interviews to what extent (if any) the statistical tests were pre-planned. I'd have thought the obvious thing would be to do a series of pre-planned trials using the new hardware, along the lines of the GCP formal hypothesis series. (Though if these levels of statistical significance were reproduced, only a handful of trials would be required.)
Instead, Radin gives the impression that rather than following up this remarkable result, he has embarked on
a big project involving the analysis of sentiment in tweets to try to predict shootings in the USA. I find that very difficult to understand.