More on calculating probabilitiesThis is an elementary but popular fallacy about probability theory. If two independent events each have a known probability such as one-thousandth, the chance of their both occurring together is indeed obtained by multiplying the two probabilities giving in the example one-millionth. But they must be independent: the chance of one cannot be altered by tampering with that of the other – such as ensuring its certainty.
This multiplication rule is one of the two great pillars of probability theory. The other, the addition rule, says that given two mutually exclusive events (such as rolling a one or two with a dice – both cannot be rolled), then the chance of either occurring is the sum of their probabilities. In this case each has a 1/6 probability, so if either one or two wins, the chance of success is 1/6 = 1/6 = 1/3.
These two rules, carefully used, can solve most problems of probability. They rest on a subtle sort of probabilistic "atomic theory" that takes any chance event as being compounded from a set of basic "equiprobable events". By calculating what combination of these will result in the desired chance coming up, its probability is obtained. But the notion requires subtle handling. Many misleading arguments depend on a deceptive choice of basic equiprobabilities. What is the chance of there being monkeys on Mars, for example? Either there are or are not – and it could be argued that, since nobody has yet been to Mars, these mutually exclusive situations are equally probable. Then each has half a chance of truth and there is a 50 per cent chance that there are monkeys on Mars.
More subtly, what is the chance of getting one head and one tail on two tosses of a coin? It might be reasoned that there are only three basic probabilities: two heads, head and tail, and two tails. Only one of these is favourable, so the chance is 1/3. But this is not so. There are actually four "atomic" equiprobabilities: HH, HT, TH and TT (where H stands for heads and T stands for tails), of which two are favourable. The chance is 2/4, or one half.
The chances of successIn mathematical notation, chances vary from 0 (impossible) to 1 (certain). If there are 7 equiprobable possibilities, and 2 of them will result in success, the chance of success is 2 in 7, or 2/7, or 0.2857. This can also be expressed as 28.57 per cent, or in betting parlance 2 to 5 on, or 5 to 2 against. Such figures make most intuitive sense when applied to situations that can occur many times. In a run of 7,000 trials each with a 2/7 chance of success, about 2,000 successes would be expected. A gambler would break even in the long run by accepting odds of 7 to 2 (that is $7 return for a $2 stake). Where the basic equiprobable events are clear and knowable (as in the fall of coins, dice or cards), probability theory can give unambiguous chances of success for any outcome. All casinos and gambling houses use this principle to set fixed odds that give them a small advantage.
In sports and business assessments, odds are subjective and different people guess them differently. By betting on the favorite in a horse-race with a number of unproven "outsiders", however, the gambler's chances of winning are demonstrably better. If one of the horses is known to be doped, or a rival's business strategy is known, it is possible to place investments with better-than-average insight. This is the province of game theory - the theory of competing for gains against opponents who possess assumed aims and knowledge.
In the child's game of button-button a button is hidden in one hand and the opponent has to guess which. He wins a penny if he is correct and loses one if he is wrong. What is the best strategy for the holder? If the same hand is always played, or hands are switched regularly, the opponent will soon outguess the holder. Game theory proves that the best strategy is to decide the switch at random, for example by tossing a coin before each round. This is entirely foolproof; even if the opponent discovers the strategy he cannot win more than he loses in the long run. But if two pennies are lost for a right-hand disclosure and only one penny for a left-hand one, the opponent could then win steadily by always choosing the right hand, and making on average bigger gains than losses. For this modification, game theory prescribes for the holder "weighted random switch" of 2:1 towards the left – say by tossing a die and playing to the right on 1 and 2, but to the left on 3, 4, 5 and 6.
Permutations and combinations
6/6 × 5/6 × 4/6 × 3/6 × 2/6 × 1/66or 6!/66 (see factorial) – 1/65. Clearly one is more likely to succeed with a desired combination than with a permutation.
Applications of probabilityProbability theory is plainly intimately linked with statistics. More advanced probability theory has contributed vital understandings in many fields of physics, as in thermodynamics, behavior of particles in a colloid (see Brownian motion), or molecules in a gas, and atomic physics.
In real-life conflicts such as war and business, game theory is often used for clarifying options, but seldom slavishly followed. If two people make an agreement, for example, game theory recommends to each that he double-crosses the other, for he will gain more if the other is honest. And in a world of unique events that either happen or do not, the whole concept of probability needs careful handling. Be warned by Peter Sellers parody of a politician, who "does not consider present conditions likely".
Related category PROBABILITY AND STATISTICS
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