课程: Probability Foundations for Data Science

今天就学习课程吧！

今天就开通帐号，24,700 门业界名师课程任您挑！

Exponential distribution

Exponential distribution

课程: Probability Foundations for Data Science

开始一个月试用 购买团队方案

Exponential distribution

“

- [Lecturer] The next distribution is the exponential distribution. The exponential distribution works with continuous random variables where it models the time between events in a Poisson process. A Poisson process is where events occur independently and continuously at a constant average rate. This distribution is positively skewed. The exponential distribution has one variable lambda, which is called the rate parameter. The exponential distribution is represented by the following probability density function where lambda is greater than zero. So you'll see your function is equal to Lambda multiplied by E to the negative Lambda multiplied by X. This equation represents the probability of the time between events that occur within a specific interval. Note that the rate parameter controls how quickly the probability density decreases exponentially as X increases. This function should create a backwards J shape if you visualize it. The exponential distribution has four main properties.…

内容