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Excel Worksheet Functions for Correlation

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2016-10-21 12:51:16
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Excel provides two worksheet functions for calculating correlation — and, they do exactly the same thing in exactly the same way! Why Excel offers both CORREL and PEARSON is unclear, but there you have it. Those are the two main correlation functions.

The others are RSQ, COVARIANCE.P, and COVARIANCE.S. RSQ calculates the coefficient of determination (the square of the correlation coefficient). COVARIANCE.P determines covariance. It uses N-1. COVARIANCE.S uses N.

CORREL and PEARSON

Here, you see an example of CORREL along with the Function Arguments dialog box for CORREL.

CORREL The Function Arguments dialog box for , along with data.

To use this function, follow these steps:

  1. Type the data into cell arrays and select a cell for CORREL’s answer. Enter the SAT data into C3:C22 and the GPA data into D3:D22, and selected F15. SAT has been defined as the name of C3:C22 and GPA as the name of D3:D22.
  2. From the Statistical Functions menu, select CORREL to open its Function Arguments dialog box.
  3. In the Function Arguments dialog box, enter the appropriate values for the arguments. In the Array1 box, enter SAT — the name assigned to the cell range (C3:C22) that holds the scores for one of the variables. In the Array2 box, enter GPA — the name assigned to the cell range (D3:D22) that holds the scores for the other variable. With values entered for each argument, the answer, 0.81662505, appears in the dialog box.
  4. Click OK to put the answer into the selected cell. Selecting PEARSON instead of CORREL gives you exactly the same answer, and you use it exactly the same way.

RSQ

If you have to quickly calculate the coefficient of determination (r2), RSQ is the function for you. There really is no particular need for this function because it’s easy enough to use CORREL and then square the answer.

Here’s what the Excel Formula bar looks like after you fill in the RSQ Function Arguments dialog box for this example:

=RSQ(GPA,SAT)

In terms of the dialog box, the only difference between this one and CORREL (and PEARSON) is that the boxes you fill in are called Known_y's and Known_x's rather than Array1 and Array2.

COVARIANCE.P and COVARIANCE.S

As far as calculating correlations go, there is really no need for these formulas.

You use these functions the same way you use CORREL. After you fill in the Function Arguments dialog box for COVARIANCE.P for this example, the formula in the Formula bar is

=COVARIANCE.P(SAT,GPA)

If you want to use this function to calculate r, you divide the answer by the product of STDEV.P(SAT) and STDEV.P(GPA). It’s up to you to figure out how you’d use COVARIANCE.S to calculate r. It’s unclear why you’d bother with all of this when you can just use CORREL.

About This Article

This article is from the book: 

About the book author:

Joseph Schmuller, PhD, is a cognitive scientist and statistical analyst. He creates online learning tools and writes books on the technology of data science. His books include R All-in-One For Dummies and R Projects For Dummies.