Which of the following formula is used to compute covariance between two variables X and Y?
A)cov (X,Y)= $\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) \left( y _ { i } - \mu _ { y } \right) } { N }$
B)cov (X,Y)= $\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) ^ { 2 } } { N }$
C)cov (X,Y)= $\sum_{i=1}^{N} \frac{\left(x_{i}-\mu_{x}\right)^{2}}{y_{i}-\mu_{y}}$

D)cov (X,Y)= $\frac{\sum_{i=1}^{N}\left(x_{i}-\mu_{x}\right)^{2}}{N^{2}}$

Question

Which of the following formula is used to compute covariance between two variables X and Y?
A)cov (X,Y)= $\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) \left( y _ { i } - \mu _ { y } \right) } { N }$
B)cov (X,Y)= $\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) ^ { 2 } } { N }$
C)cov (X,Y)= $\sum_{i=1}^{N} \frac{\left(x_{i}-\mu_{x}\right)^{2}}{y_{i}-\mu_{y}}$

D)cov (X,Y)= $\frac{\sum_{i=1}^{N}\left(x_{i}-\mu_{x}\right)^{2}}{N^{2}}$

Quizplus · Accepted Answer

Option A is the correct formula to compute the covariance between two variables X and Y. It takes into account the difference between each data point and the mean of both X and Y, multiplied together and averaged over the total number of data points. This formula is commonly used in statistics to measure the degree to which two variables are linearly related. The other options (B, C, and D) are incorrect formulas for computing covariance.

Which of the Following Formula Is Used to Compute Covariance ∑i=1N(xi−μx)(yi−μy)N\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) \left( y _ { i } - \mu _ { y } \right) } { N }N∑i=1N​(xi​−μx​)(yi​−μy​)​

Which of the Following Formula Is Used to Compute Covariance $\frac { \sum _ { i = 1 } ^ { N } \left( x _ { i } - \mu _ { x } \right) \left( y _ { i } - \mu _ { y } \right) } { N }$