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The following steps are the basics to calculate the covariance. This is all part of covariance equation.

- First step is to calculate the mean of first variable (X) and second variable (Y)
- Multiply each data entry point of first (X) with second variable (Y).
- Next step is to calculate the mean of obtained terms in step II (XY).
- After this step we need to find out the product of mean of X and Y.
- Last step is to find out the difference between the mean obtained in step 4 (X and Y) from the mean obtained in step 3 (XY).

This calculated difference is covariance.

Solution: Given two variables, X (1, 1, 1, 1) and Y (2, 2, 2, 2)

To find: - Covariance

Step 1:- Mean of X = (1+ 1+ 1+ 1)/4 = 4/4 = 1

Mean of Y = (2+ 2+ 2+ 2)/4 = 8/4 = 2

Step 2:- Now we need each data point of X and Y that is (2x1, 2x1, 2x1, 2x1) = (2, 2, 2, 2)

Step 3:- Now the mean of XY = (2+2+2+2)/4 = 8/4 = 2

Step 4:- Next step is to multiply the mean of X and Y, that is 2 x 1= 2

Since covariance is zero, therefore it is known as uncorrelated.

Solution: Given two variables, X (4, 4, 2, 2) and Y (2, 2, 2, 2)

To find: - Covariance

Step 1:- Mean of X = (4+ 4+ 2+ 2)/4 = 12/4 = 3

Mean of Y = (2+ 2+ 2+ 2)/4 = 8/4 = 2

Step 2:- Now we need each data point of X and Y that is (2x4, 2x4, 2x2, 2x2) = (8, 8, 4, 4)

Step 3:- Now the mean of XY = (8+8+4+4)/4 = 24/4 = 6

Step 4:- Next step is to multiply the mean of X and Y, that is 3 x 2= 6

Since covariance is zero, therefore it is known as uncorrelated.