## What Is Correlation Matrix In Excel?

The

Correlation Matrix in Excelis a square and symmetrical table containing the correlation coefficients of the specified variables. And the matrix helps analyze the degree of the linear relationship between all the possible variable pairs.

Users can use the

Excel Correlation Matrixto summarize a massive dataset and determine correlation patterns to make decisions accordingly.

For example, the table below contains the values of two variables in a dataset.

To **calculate Correlation Matrix in Excel** to analyze the relationship pattern between the two specified variables, we can use the **Correlation **analysis tool in the **Analysis ToolPak** feature in the **Data **tab to achieve the required **correlation matrix.**

The above **Correlation Coefficient Matrix Excel **shows that the correlation coefficient for the variables X and Y is **0.61316**, indicating a positive correlation between the variables. In other words, the two given variables tend to advance in the same direction but at different rates.

However, as the value is not close to +1, the association or correlation between the variables is moderate. Also, the section above the matrix diagonal is empty, as the matrix is symmetric, and the coefficients in the top and bottom sections of the diagonal will be the same.

##### Table of contents

###### Key Takeaways

- The
**Correlation Matrix in Excel**is a square matrix containing the correlation coefficients for all variable pairs in the given dataset. And it is symmetric along its diagonal. The matrix helps assess the correlation strength between two variables. - Users can use the
**Correlation Matrix**as inputs in analyses, such as confirmatory factor research. - We can create an
**Excel Correlation Matrix**using the**Correlation**analysis tool in the**Analysis ToolPak**feature from the**Data**tab. On the other hand, the inbuilt**CORREL**function also helps build the correlation matrix in a worksheet.

**Explanation Of Correlation Matrix In Excel**

A **Correlation Matrix in Excel **gives the correlation coefficients for pairs of variables in a dataset. And the values help determine the strength of the relationship between each pair of variables.

Furthermore, the correlation coefficient can take the values +1, -1, 0, and any value from -1 to +1.

- The value of +1 symbolizes a perfect positive correlation, signifying that as one variable increases, the other variable increases at the same rate. Otherwise, as one variable decreases, the other decreases at the same rate.
- The value of -1 represents a perfect negative correlation, that says, if one variable increases, the other decreases at the same rate, & as one variable decreases, the other increases at the same rate.
- The value of 0 indicates no correlation between the variables. In other words, the two entities will be independent of each other.
- A coefficient correlation lying between -1 to 1 indicates that the variables move at a similar rate but not at the same rate.

**Excel VBA – All in One Courses Bundle (35+ Hours of Video Tutorials)**

**Excel VBA – All in One Courses Bundle (35+ Hours of Video Tutorials)**

If you want to learn Excel and VBA professionally, then Excel VBA All in One Courses Bundle (35+ hours) is the perfect solution. Whether you’re a beginner or an experienced user, this bundle covers it all – from Basic Excel to Advanced Excel, Macros, Power Query, and VBA.

### Characteristics Of Correlation Matrix In Excel

The characteristics of the **Correlation Coefficient Matrix Excel **are as follows:

- The matrix is always square. It implies that the total number of rows and columns is equal.
- An
**Excel Correlation Matrix**is symmetric, implying that the correlation matrix and its transpose are equal. - When we
**calculate Correlation Matrix in Excel**, we achieve a positive semi-definite matrix. It implies that the product of a column vector, the correlation matrix, and the transpose of the column vector will equal or exceed 0. - When the correlation coefficient is nearer to +1 or -1, it indicates a stronger relationship between the variable pair.

### How To Create A Correlation Matrix In Excel?

Considering the **Excel Correlation Matrix significance**, there are two methods to create a correlation matrix in a worksheet, namely:

**Correlation Matrix with Analysis ToolPak.****Correlation Matrix for Multiple Variables.**

**Method #1 – Correlation Matrix with Analysis ToolPak**

We can build a correlation matrix using the **Analysis ToolPak** feature in the **Data **tab.

But first, if the **Data Analysis** feature required to access the **Analysis ToolPak** option is unavailable in the **Data** tab, as shown in the image below, then we must install it.

The steps to enable the** Data Analysis** feature are as follows:

**Step 1: **Open a worksheet, and click the **File **tab. And then click **Options** to open the **Excel Options** window.

**Step 2: **Click the Excel **Add-ins** tab in the **Excel Options** window.

And then click **Go** to open the **Add-ins** window.

**Step 3: **Check the **Analysis ToolPak **option in the available **Add-ins** listed in the **Add-ins** window. And click the **OK** button.

Now, the **Data Analysis **feature will be visible in the **Data **tab, which we can use to access the **Analysis ToolPak** option and create the required correlation matrix.

For example, the table below contains the total hours a student spent studying for exams and the scores the student secured in the corresponding tests.

And let us consider the **Total Hours Spent Studying (hrs.) **andthe** Test Score (100)** as the two specified variables.

So, the method to generate the correlation matrix in a worksheet for the given variables to understand the dependency between them is as follows:

**Step 1: **Select the **Data** tab and then the **Data Analysis** feature to open the **Data Analysis **window.

**Step 2: **The **Data Analysis** window lists the analysis tools, from which we must choose **Correlation**.

And clicking **OK **will open the **Correlation** window.

**Step 3: **Update the **Input Range** field with the source data range, which includes the column headings.

And as the given data is in columns B and C, the **Grouped By** field should be **Columns**.

Furthermore, as we include the column headers in the input data range, check the labels option to view the variable names in the output matrix.

Finally, select the **Output options **as **Output Range** to view the output in the current worksheet.

And enter the target cell reference in excel in the **Output Range **field, where we must display the required correlation matrix.

Thus, clicking **OK** in the **Correlation **window will result in the following correlation matrix in the target cell E2.

The resulting correlation matrix shows that the correlation coefficient for the variables, **Total Hours Spent Studying (hrs.) **and **Test Score (100)**, is **0.853531604**.

The value is close to **+1**. Thus, the correlation between the variables is significantly positive. In other words, the more hours the student spends studying for the exams, the better score he will secure.

Moreover, all the values in the matrix diagonal are 1, indicating that each variable perfectly correlates with itself.

#### Method #2 – Correlation Matrix for Multiple Variables

We shall see how to create a correlation matrix in a worksheet for a dataset containing multiple variables.

The table below shows the expected returns of three companies over a duration.

Consider the three companies are three variables, and their expected returns are the corresponding variables’ values.

Then, here is how to build the required correlation matrix to determine the dependency between all the possible variable pairs. Assume cell **F3** is the target cell.

**Step 1: **Select **Data** – **Data Analysis** to open the **Data Analysis **window.

**Step 2: **The **Data Analysis** window lists the analysis tools, from which we must choose **Correlation**. And clicking **OK** will open the **Correlation **window.

**Step 3: **Update the input range, **Grouped By** and label fields, and the target cell reference in the **Output Range **field in the **Correlation** window, as shown below.

And clicking **OK** in the **Correlation **window will result in the following correlation matrix in the target cell **F3**.

However, an **Excel Correlation Matrix color **can help in a more effective correlation analysis for the given variables. And for that, we can follow the below steps.

**Step 4: **Select the cell range **G4:I6**, containing the correlation coefficients, and choose **Home **– **Conditional Formatting** – **Color Scales**.

And choose the required color scale, as shown below.

Finally, clicking the highlighted color scale will give the following **Excel Correlation Matrix color**.

The Green color in the cell range **G4:I6** indicates the strongest positive correlation between the specified two variables. On the other hand, the color shifts towards Red as the positive correlation strength between the specified variables reduces.

**Interpretation Of Correlation Matrix In Excel**

In this section, we shall understand the **Excel Correlation Matrix significance** with the scenario illustrated in the previous section.

The dataset contains three variables. So, the resulting correlation matrix will be a 3×3 square matrix. And it will be diagonally symmetric.

Further, the correlation matrix shows the variables in each row’s first cell and every column heading of the resulting table. Thus, we see the three company names in cells **F4:F6 **and** G3:I3.**

And each correlation coefficient in a cell where a row and column in the matrix meet indicates the level of the linear relationship between the corresponding variables.

And here is how to analyze the correlation matrix:

**Company A**and**Company B**’s correlation coefficient:**0.603810245**

As it is positive but not close to +1, the correlation between the variables is moderately positive.- The correlation coefficient of
**Company A**and**Company C**:**0.23267814**

The correlation between the variables is negligible as the value is positive but farther away from +1. - The correlation coefficient of
**Company B**and**Company C**:**0.607188733**

As it is positive but not close to +1, the correlation between the variables is moderately positive.

Thus, when **Company B**’s expected returns improve, the expected returns at the other two companies also improve. Likewise, when **Company B**’s expected returns reduce, the expected returns of the other two companies also reduce.

Furthermore, we can use the **CORREL excel function** to create the symmetric correlation matrix. The function helps directly calculate the correlation coefficient between the two specified variables.

And the steps are as follows. Assume the target cell is **F11**, and we shall display the required correlation coefficients in the cell range **G12:I14**.

**Step 1: **Select cell **G12**, enter the **CORREL() **formula** =CORREL(B4:B8,B4:B8)**, and press

**Enter**.

**Step 2: **Select cell **H12**, enter the formula ** =CORREL(B4:B8,C4:C8)**, and press

**Enter**.

**Step 3: **Select cell **I12**, enter the formula ** =CORREL(B4:B8,D4:D8)**, and press

**Enter**.

**Step 4: **Select cell **G13**, enter the formula ** =CORREL(C4:C8,B4:B8)**, and press

**Enter**.

**Step 5: **Select cell **H13**, enter the formula ** =CORREL(C4:C8,C4:C8)**, and press

**Enter**.

**Step 6: **Select cell **I13**, enter the formula ** =CORREL(C4:C8,D4:D8)**, and press

**Enter**.

**Step 7: **Select cell **G14**, enter the formula ** =CORREL(D4:D8,B4:B8)**, and press

**Enter**.

**Step 8:** Select cell **H14**, enter the formula ** =CORREL(D4:D8,C4:C8)**, and press

**Enter**.

**Step 9: **Select cell **I14**, enter the formula ** =CORREL(D4:D8,D4:D8)**, and press

**Enter**.

The **CORREL()** in each cell in the matrix accepts the data ranges of the variables mentioned in the corresponding row and column as inputs. And it returns the variables’ correlation coefficient.

Thus, the resulting correlation matrix is the same as the one obtained using the **Correlation **option in the **Analysis ToolPak **feature, with the interpretation also being the same.

### Important Things To Note

- Ensure the given dataset does not have non-numeric values. Otherwise, we will get a warning message and be unable to obtain the
**Correlation Matrix in Excel**. - Consider we calculated a correlation matrix and then edited the source data. Then, the matrix will not update automatically. Also, clicking
**Ctrl**+**Z**will not undo the correlation matrix evaluations. For any updates in the matrix, we must delete the current one and create another matrix from the start.

**Frequently Asked Questions**

**1. Can Correlation Matrix in Excel be negative?**

The **Correlation Matrix in Excel** can be negative.

For example, the table below shows the trial results of an experiment. And the trial results are in the form of values of two variables.

To determine the degree of the linear correlation between the variables, we can calculate the correlation matrix to obtain the correlation coefficient for the variables and perform the required analysis. Assume the target cell is cell **F2**.**Step 1: **Select **Data** – **Data Analysis **to open the **Data Analysis **window.**Step 2: **The **Data Analysis** window lists the analysis tools, from which we must choose **Correlation**.

And clicking **OK** will open the **Correlation **window.**Step 3: **Update the input range, **Grouped By** and label fields, and the target cell reference in the **Output Range **field in the **Correlation** window, as shown below.

And clicking **OK** will give the following correlation matrix in the target cell.

The outcome shows that the correlation matrix is negative, with the correlation coefficient for variables 1 and 2 being negative, **-0.913414682**.

The negative value is close to -1. Thus, it implies that the correlation between the variables is strongly negative, and they move in opposite directions at similar rates.

**2. Why is Correlation Matrix in Excel used?**

The **Correlation Matrix in Excel** is used for the following applications:**•** For summarizing a massive dataset to analyze the correlations patterns.**•** As inputs in analyses such as the Exploratory Factor review and Structural Equation models.

**3. How to detect multicollinearity in Correlation Matrix in Excel?**

We can detect multicollinearity in **Correlation Matrix in Excel** by checking the correlation coefficients for the variable pairs. If the absolute correlation coefficient of two or more variables exceeds 0.7, it indicates multicollinearity in the correlation matrix.

**Download Template**

This article must help understand the **Correlation Matrix in Excel**, with its formula and examples. You can download the template here to use it instantly.

### Recommended Articles

This has been a guide to Correlation Matrix In Excel. Here we calculate correlation coefficient of multiple variables, examples & downloadable excel template. You can learn more from the following articles –

## Leave a Reply