STAT 2060 Lecture Notes - Lecture 5: Random Variable, Probability Distribution

• School: University of Guelph
• Department: Statistics
• Course: STAT 2060
• Professor: Lorna Deeth

Document Summary

1 review from week 4: continuous probability distributions f(x) The continuous probability distribution is represented by a probability density function, which is a curve that describes the likelihood of all possible values of x. The function f (x) determines the shape of this curve, with some shapes being more common than others. With continuous random variables, we are interested in determining the probability of x being in a range of values, since it is not possible for us to nd the probability of x being exactly equal to a single value. That is, we can nd: p (x < a, p (x > a, p (a < x < b) but not p (x = a) Since the probability associated with a continuous random variable x is associated with the area un- der the probability density function, and it is not possible to nd the area under a single point, the.