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.

`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.