why is correlation na in r
Correlation NA in R
In R, the cor
function is used to calculate the correlation coefficient between two variables. If there are missing values in the data, the cor
function has an argument called use
which specifies how to handle missing values. By default, it is set to "everything"
, which means that if there are any missing values in the data, the result will be NA
[3].
When the use
argument is set to "everything"
, the cor
function will return NA
if there are any missing values in the data. This is because the correlation coefficient cannot be calculated when there are missing values, and R returns NA
to indicate that the result is not available [3].
To handle missing values in the data when calculating the correlation coefficient, the use
argument can be set to "complete.obs"
. This will cause the cor
function to calculate the correlation coefficient using only complete pairs of observations, excluding any pairs that contain missing values.
In summary, when using the cor
function in R, it's important to consider how missing values should be handled by setting the use
argument appropriately to ensure the desired behavior for the correlation calculation.