CSCI 3022 Lecture 9: Lecture 09
25 Feb 2019
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Document Summary
Many real-life random processes must be modeled by random variables the can take on continuous (ex: not discrete) value. Final grades in a class: x (cid:15464) Time between people checking out in a line at the store: x (cid:15464) Ex: suppose your friend asks you what the temperature will be like today. Specifically, they want to know what the probability that the temperature is between 70 and 80 , so they can decide whether or not to wear shorts. A random variable x is continuous if for some function f: r (cid:736) r and for any numbers a and b with a (cid:15457) b, The function f must satisfy: (1) f(x) (cid:15458) 0 for all x (2) We call f the probability density function (pdf) of x. Ex: suppose you have some reason to believe that the temperature is equally likely to be anywhere between 55 and 81 . Find the probability density function (pdf) for x.
