An Introduction to Probability and Random Processes by Gian-Carlo Rota, Kenneth Baclawski

By Gian-Carlo Rota, Kenneth Baclawski

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Further, a probability of any event E consisting of t outcomes, equals P {E} = ωk ∈E 1 n =t 1 n = number of outcomes in E . 21. Tossing a die results in 6 equally likely possible outcomes, identified by the number of dots from 1 to 6. 5), we obtain, P {1} = 1/6, P { odd number of dots } = 3/6, P { less than 5 } = 4/6. ♦ The solution and even the answer to such problems may depend on our choice of outcomes and a sample space. 5) does not apply. 22. A card is drawn from a bridge 52-card deck at random.

7 Chebyshev’s inequality . . . . . . . . . . . . . . . . . 8 Application to finance . . . . . . . . . . . . . . . . . . 4 Families of discrete distributions . . . . . . . . . . . . . . . . . 1 Bernoulli distribution . . . . . . . . . . . . . . . . . . 2 Binomial distribution . . . . . . . . . . . . . . . . . . 3 Geometric distribution . . . . . . . . . . . . . . .

4 Variance and standard deviation . . . . . . . . . . . . 5 Covariance and correlation . . . . . . . . . . . . . . . 6 Properties . . . . . . . . . . . . . . . . . . . . . . . . 7 Chebyshev’s inequality . . . . . . . . . . . . . . . . . 8 Application to finance . . . . . . . . . . . . . . . . . . 4 Families of discrete distributions . . . . . . . . . . . . . . . . . 1 Bernoulli distribution .

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