Signal to Noise Ratio

The Global Consciousness Project is a long term effort to learn about a subtle phenomenon or effect. We are looking where many sensible people will say there is nothing to see, in other words, we're at work near or at the boundaries of what we know. The first question is, then, whether there is an effect, and since it is at best a subtle one, we are in the realm of the "low signal to noise ratio." Often written simply as low S/N, this is a familiar region for many sciences, so there are tools, mainly statistical, but also philosophical to deal with it.

The GCP effects are generally very small compared with noise -- it's a classic situation, and there are implications. The S/N ratio is so small we can't reliably detect effects of even major events if we look at only one case. We need a dozen or two events of a similar kind to get reliable statistical estimates. The implication is that individual personal influences on the system will be too small to detect, although they may be contributing to the overall "global consciousness." Similarly, the effect of "local" influences is difficult or impossible to detect or measure, though this is an idea that comes naturally to many people. The GCP instrument is designed for a different purpose.

The primary measure we use computes a composite across the whole network which is an average correlation of pairs of eggs. This means that a local influence (close proximity) actually doesn't quite mean what it seems to in terms of our measure. That is, if there is an influence on an egg in Japan, and an influence on one in Alaska, those inflences won't affect the correlation -- unless they are similar, synchronized influences. Of course that describes what we have in mind when we talk about global consciousness operationally. We say that global consciousness happens when large numbers of people are engaged by the event and have the same response; they share thoughts and emotions. This shared response may reach a level of coherence that is capable of supporting an information (or consciousness) field that becomes the source of the effects we measure.

Returning to the S/N ratio, we can see that the "ifs" are numerous. More to the point, we know from more than a decade of research that the average effect size is about a third of a standard deviation. This means that we have to put many individual events (hypothesis tests) together in a kind of meta-analysis to achieve reliable statistics. We need at least a dozen strong cases, or several dozen on average to draw sensible conclusions about whether there is any "there there" as Gertrude Stein so colorfully put it.

Here is a caveat which appears after each analysis (to cool down the excitment over an apparently off-the-scale result, or to assuage the disappointment over a visualized flatline.)

It is important to keep in mind that we have only a tiny statistical effect, so that it is always hard to distinguish signal from noise. This means that every "success" might be largely driven by chance, and every "null" might include a real signal overwhelmed by noise. In the long run, a real effect can be identified only by patiently accumulating replications of similar analyses.

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