Question

What is E in covariance?

Answer 1

Step-by-step explanation:

yn. For two random variables x and y having means E{x} and E{y}, the covariance is defined as: Cov(x,y) = E{[ x - E(x) ][ y - E(y) ]} The covariance calculation begins with pairs of x and y, takes their differences from their mean values and multiplies these differences together.

Answer 2

Answer:

E(X) = μ is the expected value (the mean) of the random variable X and. E(Y) = ν is the expected value (the mean) of the random variable

Step-by-step explanation:

yn. For two random variables x and y having means E{x} and E{y}, the covariance is defined as: Cov(x,y) = E{[ x - E(x) ][ y - E(y) ]} The covariance calculation begins with pairs of x and y, takes their differences from their mean values and multiplies these differences together.