Because intelligent design theory is rooted in information theory which in turn relies in some part on probability, ID theorists study the probability of a given sequence of findings or events in nature. A recent article, “Chasing coincidences” in *Nautilus,* maybe of interest here:

Probabilities are defined as relative measures in something called the “sample space,” which is the set of all possible outcomes of an experiment—such as drawing a card out of a well-shuffled deck, rolling a fair die, or spinning a roulette wheel. We generally assume that every elementary outcome of the experiment (any given card or any of the possible numbers, in the case of dice or roulette) has an equal likelihood, although the theory can handle sample spaces with varying likelihoods as well. If we can define a sample space in a real-world situation that may not involve a game of chance, then we can measure probabilities through this sample space.

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Coincidences and their analysis have led to important academic research in all areas where probability plays a role. Persi Diaconis, professor of statistics at Stanford University, describes extremely unlikely coincidences as embodying the “blade of grass paradox.” If you were to stand in a meadow and reach down to touch a blade of grass, there are millions of grass blades that you might touch. But you will, in fact, touch one of them. The a priori fact that the blade you touch will be any particular one has an extremely tiny probability, but such an occurrence must take place if you are going to touch a blade of grass. More.

Yes, and by the same token, if patterns emerge about which ones got touched and how, the tiny probabilities may point in a direction or to a pattern: