Random Variable2

Random Variable ======================
We know that discrete random variable is one which may take on only a countable number of distinct values such as 0,1,2,3,4,........ Discrete random variables are usually (but not necessarily) counts. Example Suppose a variable X can take the values 1, 2, 3, or 4. The probabilities associated with each outcome are described by the following table: Outcome Probability 0.1 0.3 0.4 0.2 The probability that X is equal to 2 or 3 is the sum of the two probabilities: P(X = 2 or X = 3) = P(X = 2) + P(X = 3) Assign the discrete random variable X to the values 1, 2, 3, 4, 5, or 6 as follows: if 05, X=6. The probability distribution of a discrete random variable is a list of probabilities associated with each of its possible values. It is also sometimes called the probability function or the probability mass function. All random variables (discrete and continuous) have a cumulative distribution function. It is a function giving the probability that the random variable X is less than or equal to x, for every value x. For a discrete random variable, the cumulative distribution function is found by summing up the probabilities