# Covariance for X = 11, 13, 15, 17 & 14 and Y = 12, 23, 14, 16 & 15

Co*variance* calculation summary for two random variables X = 11, 13, 15, 17 & 14 and Y = 12, 23, 14, 16 & 15 to estimate the strength of linear inter-dependence between them.

Calculation Summary | |
---|---|

Dataset X | 11, 13, 15, 17 & 14 |

Dataset Y | 12, 23, 14, 16 & 15 |

COV(X, Y) | 0.6 |

## Example with Steps for COV(X, Y) = 0.6

The below workout with step by step calculation may help grade school students, beginners or learners to understand how to estimate the covariance(X, Y) for random variables X = 11, 13, 15, 17 & 14 and Y = 12, 23, 14, 16 & 15

__Workout :__

step 1 Address the formula, input parameters and values

X = 11, 13, 15, 17 & 14

Y = 12, 23, 14, 16 & 15

Number of inputs = 5

step 2 Formula for Covariance(X, Y)

COV (X, Y) = 1/n n ∑ i = 1 (x

_{i}- x)(y

_{i}- y)

step 3 Apply the values in above formula

COV (X, Y) = 1/n{ (11 - 14) x (12 - 16) + (13 - 14) x (23 - 16) + . . . . + (14 - 14) x (15 - 16) }

= 1/5{ (-3) x (-4) + (-1) x (7) + . . . . + (0) x (-1) }

= 1/5{ (12) + (-7) + . . . . + (-0) }

=3/5

COV(X, Y) = 0.6

0.6 is the covariance for X = 11, 13, 15, 17 & 14 and Y = 12, 23, 14, 16 & 15