# COVAR

### Definition of COVAR

Calculates the covariance of a dataset.

### Sample Usage

`COVAR(A2:A100,B2:B100)`

### Syntax

`COVAR(data_y, data_x)`

`data_y`

- The range representing the array or matrix of dependent data.`data_x`

- The range representing the array or matrix of independent data.

### Notes

Any text encountered in the

`value`

arguments will be ignored.Positive covariance indicates that the independent data and dependent data tend to change together in the same direction; negative indicates that they tend to change together in the opposite direction (i.e. increase in one leads to decrease in the other). The magnitude of covariance is difficult to interpret - use

`CORREL`

or`PEARSON`

, the normalized version of`COVAR`

, to gauge strength of linear correlation.

### See Also

`STEYX`

: Calculates the standard error of the predicted y-value for each x in the regression of a dataset.

`SLOPE`

: Calculates the slope of the line resulting from linear regression of a dataset.

`RSQ`

: Calculates the square of r, the Pearson product-moment correlation coefficient of a dataset.

`INTERCEPT`

: Calculates the y-value at which the line resulting from linear regression of a dataset will intersect the y-axis (x=0).

`FORECAST`

: Calculates the expected y-value for a specified x based on a linear regression of a dataset.

`COVAR`

: Calculates the covariance of a dataset.

`CORREL`

: Calculates r, the Pearson product-moment correlation coefficient of a dataset.

### In order to use the COVAR formula, start with your edited Excellentable:

### Then type in the COVAR Formula in the area you would like to display the outcome:

### By adding the values you would like to calculate the COVAR formula for, Excellentable will generate the outcome: