KP223 Lecture Notes - Lecture 3: Random Variable, Exponential Distribution, Cumulative Distribution Function

• School: WLU
• Department: Kinesiology & Physical Education
• Course: KP223
• Professor: Diane Gregory

Document Summary

Note: not all material covered in lecture is covered on the labs. P (x = a) = 0 due to limitations on ability to measure. The area under the curve of the pdf gives the probability that x will lie within a certain interval. I. e. p (a < x < b) is determined by calculating the area under f (x) over [a,b]. P (a < x < b) = f (x) dx: the cumulative distribution function (c. d. f. ) Fx (x) represents the probability that a random variable x will be found at a value less than or equal to x: Fx (x) = p (x x) = f (t) dt, x r (cid:90) x. Note that p (a < x < b) = fx (b) fx (a) For a continuous random variable x: the mean or expected value of x is. X = e(x) : the variance of x is (cid:90) .