After hearing that Ian Banks died recently, I decided that I would finally try reading some of his books. I had the book 'Consider Pheblas' recommended to me as a good place to start. I quite enjoyed it, except for this one passage near the introduction: (emphasis mine)
There were in excess of eighteen trillion people in the Culture, just about every one of them well nourished, extensively educated and mentally alert, and only thirty or forty of them had this unusual ability to forecast and assess on a par with a wellinformed Mind (of which there were already many hundreds of thousands). It was not impossible that this was pure luck; toss eighteen trillion coins in the air for a while and a few of them are going to keep landing the same side up for a long, long time.
I had to stop and actually calculate the chances of this happening because it bothered me so much. Yes, so maybe I'm a little bit too much of a probability geek . . .
Here's the basic assumptions I'm going to make:
 There are 18 trillion people in the Culture.
 Each of the people is represented by a perfectly fair coin.
 The coins are flipped one hundred times.
 A person is considered to be a Culture Referer (i.e. one of the thirty or forty) iff their coin shows the same side across at least 90 of the 100 coinflips.
The third point might be the one with the most contention, but it seems reasonable in context, especially given later passages such as:
. . . who could give you an intuitive idea of what was going to happen, or or tell you why [they] thought that something which had already happened had happened the way it did, and almost certainly turn out right every time.
Well. Let's see about that, shall we?
The calculation
Let be a random variable denoting the number of people in the Culture who are Referers. We can then express as a sum of indicator random variables , which are 1 if person is a referer, and 0 otherwise.
By assumptions made above, we know that is 1 iff a coin, flipped 100 times, shows the same side at least 90 times. There are twenty possible numbers of heads/tails in a flip sequence that will give this result: 0 heads/100 tails, 1 head/99 tails, ..., 10 heads/90 tails, 90 heads/10 tails, 91 heads/9 tails, ..., 100 heads/0 tails.
Consider a case with heads and tails. There are possible sequences that will result in this summation. Hence, the number of sequences that will result in at least 90 of the same side showing is:
So, the probability of one fair coin showing the same side ninety times or more out of a hundred is . That is to say, for arbitrary . But, as is an indicator rv, that is also its expected value.
But since is the sum of all the , and expectation is linear, we can conclude that the expected number of coins, from the eighteen trillion, to show the same side at least 90% of the time will be:
Supposedly, there are thirty or forty of these. How about ballparking the probability of the existence of twenty Referers via a tail bound?
Tailbound
One way to state a Chernoff bound ^{1} is that, for independent Poisson trials, and , that
If we substitute an appropriate into this equation  for the probability of getting 20 such Referers  we get that
And this is for 20. If you set the target to be 30 Referers instead, you find that the probability is .
Summary
At this point, I think it's safe to say that the analogy status is busted. The concept of a Referer is an interesting one, and I don't actually think it's terribly unrealistic, given a large enough population base to draw from.
But sequences of coins are a lot more predictable than one might think.
 ethereal

See, for example, 'Randomized Algorithms' by Motwani and Raghaven, Theorem 4.1 on pg. 68. ↩