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!
Expectation of continuous random variables
课程: Probability Foundations for Data Science
Expectation of continuous random variables
- [Instructor] Next, let's learn about expectation for continuous random variables. Remember, a continuous random variable contains any value within a specified range or interval of values. For continuous random variables, the expectation is the weighted average of all possible outcomes for the random variable by integrating all those values. Let's look at the formal equation used for finding the expectation of a continuous random variable. You'll have a continuous random variable with infinite possible values in a defined range. This range goes from negative infinity to positive infinity. The expectation is represented by the following probability density function. So here you see if the expectation is equal to the integral from negative infinity to positive infinity with X multiplied by your function F of X. Let's review a few examples to solidify this concept. Let's consider continuous random variable X with the PDF of 2X between the values of zero to one and zero otherwise. To…
内容
-
-
-
-
(已锁定)
Expectation4 分钟 3 秒
-
(已锁定)
Expectation of discrete random variables6 分钟 22 秒
-
(已锁定)
Expectation of continuous random variables5 分钟 31 秒
-
(已锁定)
Conditional expectation6 分钟 20 秒
-
(已锁定)
Variance and standard deviation3 分钟 48 秒
-
(已锁定)
Discrete vs. continuous dispersion4 分钟 57 秒
-
(已锁定)
Covariance6 分钟 53 秒
-
(已锁定)
Correlation5 分钟 6 秒
-
(已锁定)
-
-
-
-
-
-