Microsoft Office Tutorials and References
In Depth Information
I am somewhat jealous that Microsoft has named an obscure function
after fellow Excel consultant Chip Pearson. I am lobbying Mi-
crosoft for the inclusion of a JELEN function, possibly used to
measure the degree of laid-backness caused by the gel in your shoe
insoles. Seriously, Chip Pearson s website is one of the best estab-
lished sources of articles on the Web about Excel. To peruse the art-
icles, visit .
The Pearson product moment correlation coefficient, named after Karl
Pearson, returns a value from 1.0 to +1.0. The calculation could make your
head spin, but the important thing to know is that a PEARSON value closer
to 1 or 1 means that a linear relationship exists. A value of 0 indicates no
correlation between the independent and dependent variables.
The PEARSON function returns the Pearson product moment correlation
coefficient, r, a dimensionless index that ranges from 1.0 to 1.0, inclusive,
and reflects the extent of a linear relationship between two data sets.
The PEARSON function takes the following arguments:
array1 This is a set of independent values.
array2 This is a set of dependent values.
The arguments must be either numbers or names, array constants, or referen-
ces that contain numbers. If an array or a reference argument contains text,
logical values, or empty cells, those values are ignored; however, cells
that contain the value 0 are included. If array1and array2are empty or
have a different number of data points, PEARSON returns an #N/A error.
The result of PEARSON is also sometimes known as r. Multiplying PEARSON
by itself leads to the more famous r-squared test.
Using RSQ
to Determine the Strength of a Linear Relationship
r-squared is a popular measure of how well a regression line explains the
variability in the y values. It is popular because the values range from 0
RSQ to Determine the Strength of a Linear Relationship
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