Correlation measures the degree to which two variables move in relation to each other. High positive correlations mean that the two variables tend to increase together at the same time, while high negative correlations show that they move apart at the same time. There are several different kinds of correlation calculations in Microsoft Excel, but the most common is the CORREL function.
The CORREL function returns the correlation coefficient for two sets of data. Technically speaking, it actually returns the Pearson productmoment correlation coefficient. The range of possible values for CORREL rests between +1.0 (perfectly positively correlated) and 1.0 (perfectly negatively correlated). A return value of zero indicates that no correlation exists in the data.
Using CORREL in Excel
The Data Analysis Toolpak makes it simpler and faster to execute ratios and correlations in Excel. Those without the Toolpak use the standard CORREL function:
= CORREL (array 1, array 2)
There may be some rounding errors in pre2003 versions of Excel, but those errors have been fixed in later editions.
The first step in calculating correlation is to have two data arrays. Arrays are sets of numeric values that can be assigned to one variable. For example, suppose someone wanted to find the correlation between height and weight among 30 students. Each measured height could become a value for Variable X and each corresponding weight could be a value for Variable Y.
In Excel, all Variable X values could be listed in Column B, descending from Row 2 to Row 31. All Variable Y values could be listed in Column C from Row 2 to Row 31. Every row would contain the height and weight of one student. In a separate cell, the following formula would be entered:
= CORREL (B2:B31, C2:C31)
This returns the Pearson correlation between the two data arrays. Excel only returns the statistical value of the correlation; it cannot interpret its significance or meaning. This is true for all financial operations in Excel.

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