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Step-by-step explanation:
The fundamentals
A continuous random variable can take infinite values in the range associated function of that variable. Consider [tex]f\left( x \right)f(x)[/tex] is a function of a continuous random variable within the range [tex]\left[ {a,b} \right][a,b][/tex] , then the total probability in the range of the function is defined as:
[tex]\int\limits_a^b {f\left( x \right)dx} = 1 a∫b f(x)dx=1[/tex]
The probability of the function [tex]f\left( x \right)f(x)[/tex] is always greater than 0. The cumulative distribution function is defined as:
[tex]F\left( x \right) = P\left( {X \le x} \right)F(x)=P(X≤x)[/tex]
The cumulative distribution function for the random variable X has the property,
[tex]0 \le F\left( x \right) \le 10≤F(x)≤1[/tex]
The probability density function for the random variable X has the properties,
[tex]\\\begin{array}{c}\\{\rm{ }}f\left( x \right) \ge 0\\\\\int\limits_{ - \infty }^\infty {f\left( x \right)dx} = 1\\\\P\left( E \right) = \int\limits_E {f\left( x \right)dx} \\\end{array} f(x)≥0[/tex]
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