Microsoft Office Tutorials and References
In Depth Information
Deviating from the Middle
increases (or decreases), then data set B also increases (or decreases). A
negative value means that the two data sets tend to move in opposite
directions: When A increases, B decreases, and vice versa. The covariance’s
absolute value reflects the strength of the relationship.
When COVARIANCE.S or COVARIANCE.P returns 0, there is no relationship
between the two sets of data.
Sales of bread will likely create sales of butter; they’re somewhat related. In
other words, the amount of butter a store sells is likely to follow the amount
of bread it sells — more bread, more butter:
Day
Loaves of Bread Sold
Tubs of Butter Sold
Monday
62
12
Tuesday
77
15
Wednesday
95
26
As bread sales increase, so do sales of butter. Therefore, sales of butter are
expected to have a positive relation to sales of bread. These items
complement each other. In contrast, bread and muffins compete against each other.
As bread is purchased, the sales of muffins likely suffer because people will
eat one or the other. Without even using any function, you can conclude that
bread sales and butter sales move in the same direction and that bread sales
and muffin sales move in differing directions. But by how much?
Figure 9-12 shows an example that measures snowfall and the number of
customers coming into a store. Two covariance calculations are given — one
for snowfall between 0 and 3 inches, and one for snowfall between 0 and 8
inches.
Figure 9-12:
Using
COVARIANCE
to look for a
relationship
between
two data
sets.
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