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Bernoulli distribution, discrete probability distributions, random variables

A single coin is an example of a Bernoulli" distribution. This probability distribution limits values of the random variable to exactly two discrete values, one with probability p, and the other with the probability (1-p). For the coin, the two values are heads p, and tails (1-p), where p = 0.5 for a fair coin. [Pg.8]

A discrete distribution function assigns probabilities to several separate outcomes of an experiment. By this law, the total probability equal to number one is distributed to individual random variable values. A random variable is fully defined when its probability distribution is given. The probability distribution of a discrete random variable shows probabilities of obtaining discrete-interrupted random variable values. It is a step function where the probability changes only at discrete values of the random variable. The Bernoulli distribution assigns probability to two discrete outcomes (heads or tails on or off 1 or 0, etc.). Hence it is a discrete distribution. [Pg.10]


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