Data were recorded from two random event generator (REG or RNG) systems in Amsterdam by Dick Bierman and one in Utrecht by Dick Bierman and Rens Wezelman. Emil Boller and Holger Boesch ran two systems in Freiburg. Richard Broughton ran two systems in Durham. Joop Houtkooper ran one system in Giessen and Paul Stevens ran one in Edinburgh. Roger Nelson ran five systems in Princeton. The available data are thus from 14 independent REG systems in seven different locations, all in the US or Europe.

All the random sources included in this study are used in professional research applications, and are qualified as nominal random sources. In previous work (Nelson, 1997; Nelson, et al, 1997) resampling techniques have shown that non-active (control) data surrounding those identified as the experimental segments, conform to theoretical expectations. Hence, the comparisons here are with theoretical expectation rather than with arbitrary control data. Several different data formats were used, and the distribution parameters had to be inferred from the data in some cases, but since the raw data closely approximate random variates in all cases, these inferences are appropriate. For example, in his typical applications, Bierman constructs a Chisquare by summing Z2 for arbitrarily defined sub-segments that are about 4.3 seconds long, rather than taking experimentally defined segments as the unit of measure. Since the pre-stated protocol specified that the measure would be the unsigned meanshift of the data taken during the time of the meditation, the appropriate analysis required a calculation of this value from the raw data provided by each of the labs. The formal experimental hypothesis was that the segment means would show larger deviations than expected by chance, i. e., that the segment variance would be increased. This hypothesis was tested by normalizing the meanshifts as Z-scores and summing the squared Z-scores to yield a Chisquare distributed quantity with degrees of freedom equal to the number of segments. The following table shows the normalized deviation of the mean for each segment, and the corresponding Chisquare (1 df) and probability, with the experimenter and the location also indicated:

Global Meditation Results by Location:
Z-Scores, Chisquares, and Probabilities
JH Giessen 0.776 0.602 1 .438
PS Edinburgh 2.81 7.930 1 .005
RB-1 Durham 0.925 0.856 1 .355
RB-2 Durham 0.100 0.010 1 .920
EB-1 Freiburg 1.382 1.910 1 .167
EB-2 Freiburg 0.137 0.019 1 .890
DB-1 Amsterdam -1.785 3.187 1 .074
DB-2 Amsterdam -0.135 0.018 1 .893
DB-3 Utrecht 0.950 0.903 1 .342
RN-1 Princeton 1.267 1.604 1 .205
RN-2 Princeton -1.677 2.812 1 .094
RN-3 Princeton 1.476 2.178 1 .140
RN-4 Princeton 0.740 0.546 1 .460
RN-5 Princeton -1.144 1.308 1 .253

All Data 1.984 23.883 14 .047

The same data can also be displayed graphically, as a cumulative Chisquare over the 14 independent recordings, which allows the relative sizes of the separate contributions to be visualized. Since the data were taken concurrently, the order in which they are displayed is arbitrary; of course, the final value of the accumulated deviation is not affected by the order. The figure also includes the expectation (df), which in this case is also the number of segments, and an envelope showing the locus of the 5% probability for so large a Chisquare as the number of samples increases. The last line in the table, and the last point on the graph both show the result when the data are concatenated across the 14 different devices. This overall accumulation represents a result that falls in the range considered significant by most scientists. It would occur by chance less than 5 times in 100 repetitions of the full experiment, and it supports the pre-stated hypothesis that the output of the various random event generators would deviate from expectation during the time of the global meditation.