By Joaquim P. Marques de Sá

This can be a certain e-book on how likelihood impacts our daily lives. It courses the reader in a virtually chronological journey in the course of the interesting and outstanding legislation of likelihood, omnipresent within the flora and fauna and in our day-by-day lives. alongside the way in which many desirable themes are mentioned. those comprise hard chance paradoxes, "paranormal" coincidences, video game odds, and reasons and results. ultimately the writer discusses probabilities and barriers of studying the legislation of a Universe immersed in probability occasions. This fascinating ebook, with its many easy-to-follow mathematical examples, will tell and entertain the scientist and non-scientist alike.

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**Additional resources for Chance: The Life of Games & the Game of Life**

**Example text**

Now, it is precisely such a law that the mathematician Jacob Bernoulli, already mentioned in Chap. 1, was able to demonstrate and Fig. 5. Ten possible evolutions of the average gain in the card game 50 3 Expecting to Win which has come to be known as the law of large numbers or Bernoulli’s law : for a sequence of random variables with the same probability law and independent from each other (in our example, no round depends on the others), the probability that the respective average deviates from the mathematical expectation by more than a certain pre-established value tends to zero.

6. Evolution of John’s average gain with the number of rounds, in six possible sequences. 3 Bad Luck Games 51 When we say ‘tends to zero’, in the law of large numbers, the meaning is that it is possible to ﬁnd a suﬃciently high value of n after which the probability of a curve exceeding a pre-speciﬁed deviation is below any arbitrarily low value we may wish to stipulate. We shall see later what value of n that is, for this convergence in probability. 3 Bad Luck Games The notion of mathematical expectation will allow us to make a better assessment of the degree of ‘bad luck’ in so-called games of chance.

In the last four matches between Mytholmroyd Athletics and Giggleswick United, Mytholmroyd have kicked oﬀ ﬁrst every time, on the toss of a coin. Which team is more likely to kick oﬀ next time? People frequently ﬁnd it diﬃcult to give the correct answer1 to such questions. When dealing with conditional events and the application of Bayes’ theorem, the diﬃculty in arriving at the right answer is even greater. Let us start with an apparently easy problem. We randomly draw a card out of a hat containing three cards: one with both faces red, another with both faces blue, and the remaining one with one face red and the other blue.