Covariance
Covariance is a measure of the joint
variability of two variables.
• A positive covariance means
that the two variables move
together.
• A covariance of 0 means that
the two variables are
independent.
• A negative covariance
means that the two
variables move in opposite
directions.
Covariance can take on values from
-∞ to +∞ . This is a problem as it
is very hard to put such numbers
into perspective.
Sample covariance formula:
In Excel,
the covariance is calculated by:
Sample covariance:
=COVARIANCE.S()
Population covariance:
=COVARIANCE.P()
Correlation
Correlation is a measure
of the joint variability of
two variables. Unlike covariance, correlation could be
thought of as a standardized
measure. It takes on values between
-1 and 1, thus it is easy for us to
interpret the result.
•
A
correlation of 1, known as perfect positive correlation, means that one variable is perfectly explained by the other.
•
A correlation of 0 means
that the variables are independent.
•
A correlation of -1, known as
perfect negative correlation,
means that one variable is explaining the other one perfectly, but they move in opposite
directions.
In Excel, correlation is calculated by:
=CORREL()
