5 Ways To Calculate Spearman Correlation In Excel

Calculating Spearman correlation in Excel can be a bit tricky, but don't worry, we've got you covered. In this article, we'll show you 5 different ways to calculate Spearman correlation in Excel, along with step-by-step instructions and examples.

What is Spearman Correlation?

Before we dive into the methods, let's quickly review what Spearman correlation is. Spearman correlation is a non-parametric measure of correlation that assesses the strength and direction of the relationship between two variables. It's commonly used when the data is not normally distributed or when the data is ordinal.

Why Use Spearman Correlation in Excel?

Excel is a powerful tool for data analysis, and calculating Spearman correlation is just one of the many statistical analyses you can perform. By using Excel, you can easily calculate Spearman correlation and visualize the results using charts and graphs.

Method 1: Using the CORREL Function

The CORREL function in Excel calculates the Pearson correlation coefficient, but we can use it to calculate Spearman correlation by using the RANK function.

Here's how:

1. Enter your data in two columns, say A and B.
2. In a new column, say C, enter the formula: =RANK.A(A1:A10,B:B)
3. In another column, say D, enter the formula: =RANK.B(B1:B10,A:A)
4. In a new cell, say E1, enter the formula: =CORREL(C1:C10,D1:D10)

Method 2: Using the RSQ Function

The RSQ function in Excel calculates the coefficient of determination, but we can use it to calculate Spearman correlation by using the RANK function.

Here's how:

1. Enter your data in two columns, say A and B.
2. In a new column, say C, enter the formula: =RANK.A(A1:A10,B:B)
3. In another column, say D, enter the formula: =RANK.B(B1:B10,A:A)
4. In a new cell, say E1, enter the formula: =RSQ(C1:C10,D1:D10)

Method 3: Using the Spearman Correlation Formula

You can also calculate Spearman correlation using the formula:

Rs = 1 - (6 * Σ(d^2)) / (n^3 - n)

where d is the difference between the ranks of the two variables, n is the number of observations, and Σ(d^2) is the sum of the squared differences.

Here's how:

1. Enter your data in two columns, say A and B.
2. In a new column, say C, enter the formula: =RANK.A(A1:A10,B:B) - RANK.B(B1:B10,A:A)
3. In another column, say D, enter the formula: =C1:C10^2
4. In a new cell, say E1, enter the formula: =1 - (6 * SUM(D1:D10)) / (COUNT(A1:A10)^3 - COUNT(A1:A10))

Method 4: Using a Macro

You can also calculate Spearman correlation using a macro. Here's an example macro that calculates Spearman correlation:

Here's how:

1. Open the Visual Basic Editor by pressing Alt + F11 or by navigating to Developer > Visual Basic.
2. In the Visual Basic Editor, click Insert > Module to insert a new module.
3. Paste the following code into the module:

Function SpearmanCorrelation(X As Range, Y As Range) As Double
    Dim n As Integer
    Dim sumd2 As Double
    n = X.Count
    sumd2 = 0
    For i = 1 To n
        sumd2 = sumd2 + (WorksheetFunction.Rank(X(i), X) - WorksheetFunction.Rank(Y(i), Y)) ^ 2
    Next i
    SpearmanCorrelation = 1 - (6 * sumd2) / (n ^ 3 - n)
End Function

4. Save the module by clicking File > Save.
5. In a new cell, say E1, enter the formula: =SpearmanCorrelation(A1:A10,B1:B10)

Method 5: Using a Third-Party Add-In

Finally, you can also calculate Spearman correlation using a third-party add-in, such as the XLSTAT add-in.

Here's how:

1. Download and install the XLSTAT add-in from the XLSTAT website.
2. In Excel, click XLSTAT > Non-parametric tests > Spearman correlation.
3. Select the data range and click OK.

Gallery of Spearman Correlation in Excel

Spearman Correlation in Excel

Conclusion

Calculating Spearman correlation in Excel can be done using various methods, from using built-in functions to creating a macro or using a third-party add-in. By following the steps outlined in this article, you can easily calculate Spearman correlation in Excel and gain insights into the relationships between your data.

We hope you found this article helpful. Do you have any questions or need further assistance? Leave a comment below or share this article with your friends and colleagues!