STAT 2507 Lecture Notes - Lecture 6: Exponential Distribution, Probability Distribution, Random Variable

• School: Carleton University
• Department: Statistics
• Course: STAT 2507
• Professor: Masoud Nasari

Document Summary

Probability distributions for continuous random variables examples: heights weights, . Length of life of a particular product distance travelled on a trip probability density function. A probability density function (f(x)) is a model for the probability distribution of a continuous random variable x. Probability density function the probability density function has the following properties: f(cid:894)x(cid:895)(cid:1096) 0. The area under the probability density function equals 1. In other words, the probability at a specific point is equal to zero. The uniform random variable is used to model the behaviour of a continuous random variable whose values are uniformly or evenly distributed over a given interval. A random variable x is said to have a uniform distribution on the real interval [c,d] or x ~ u(c: if it has the pdf. The amount of time it takes a clerk to process a certain type of application follows a uniform distribution with the following density function.