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Expectation, variance and covariance
2022-07-05 22:56:00 【YaoHa_】
expect (expectation): function f(x) On a distribution P(x), When x from P When it comes into being ,f Act on x when ,f(x) Average value . It is the probability of each possible result in the experiment multiplied by the sum of its results .
For discrete random variables , By summing, we get :
For continuous random variables , By integrating :
Standard deviation (standard deviation): When the variance is very small ,f(x) The cluster formed by the value of is close to their expected value . The square of the variance is called the standard deviation .
covariance (covariance): Measure the overall error of two variables . namely :
If the absolute value of covariance is large , It means that the variable value changes greatly , And they are also far from their respective averages . If the covariance is positive , So both variables tend to get relatively large values at the same time . If the covariance is negative , So one of the variables tends to get a relatively large value at the same time , Another variable tends to have a relatively small value , vice versa .
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