Unformatted text preview: 1. f(x) = 3e-3x for 0≤x<∞ and 0 elsewhere verify 2. f(y) = (1/12)[4+2y-y 2 ] for 0≤y≤3 and 0 elsewhere verify In this situation, we have probabilities for intervals of values, but assume that the probability of any individual point is 0. 1. in number 1 above P[.1≤X≤.4] P[X>.5] P[X=3] = 0 2. in number 2 above P[0<Y<1] P[Y>.5] The expected value of a continuous random variable is the average value that you would get if you observed the random variable many (infinitely many) times. E[X] = ∫xf(x)dx, where the integral is over the range of possible values of the variable X. Examples from above continous probability...
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- Spring '11
- Probability, Probability theory, probability density function, continuous random variable