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Covariance of Random Variables x and y

- Give Equation
- What values can Covariance take?
- Why is covariance not preferred when looking at relationships between two variables?

User MatejG
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1 Answer

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Final answer:

The covariance of random variables x and y can be positive, negative, or zero. Covariance is not preferred when looking at relationships between two variables because it does not provide a standardized measurement like correlation does.

Step-by-step explanation:

The covariance of random variables x and y can be calculated using the following equation:

cov(x, y) = E[(x - E[x])(y - E[y])]

The values that covariance can take are not limited, as it can be positive, negative, or zero. A positive covariance indicates a positive relationship between x and y, while a negative covariance indicates a negative relationship. A covariance of zero means there is no linear relationship between x and y.

Covariance is not preferred when looking at relationships between two variables because it does not provide a standardized measurement like correlation does. Covariance values are affected by the scale of the variables, making it difficult to compare the strength of the relationships between different pairs of variables.

User Galactica
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