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#reading-10-common-probability-distributions

For a **discrete random variable**, the shorthand notation is p(x) = P(X = x). For **continuous random variables**, the probability function is denoted f(x) and called **probability density function (pdf)**, or just the density. This function is effectively the continuous analogue of the discrete probability function p(x).

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**Subject 2. Probability Function**

ay, is 0 if X is continuous. In a continuous case, only a range of values can be considered (that is, 0 < X < 10), whereas in a discrete case, individual values have positive probabilities associated with them. <span>For a discrete random variable, the shorthand notation is p(x) = P(X = x). For continuous random variables, the probability function is denoted f(x) and called probability density function (pdf), or just the density. This function is effectively the continuous analogue of the discrete probability function p(x). The probability density function, which has the symbol f(x), does not give probabilities, despite its name. Instead, it is the area between the graph and the horizontal axi

ay, is 0 if X is continuous. In a continuous case, only a range of values can be considered (that is, 0 < X < 10), whereas in a discrete case, individual values have positive probabilities associated with them. <span>For a discrete random variable, the shorthand notation is p(x) = P(X = x). For continuous random variables, the probability function is denoted f(x) and called probability density function (pdf), or just the density. This function is effectively the continuous analogue of the discrete probability function p(x). The probability density function, which has the symbol f(x), does not give probabilities, despite its name. Instead, it is the area between the graph and the horizontal axi

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