# How to Create a Correlation Matrix in Q

A correlation matrix is a table of correlation coefficients for a set of variables. They are often used to determine if a relationship exists between the variables. The coefficient indicates both the strength of the relationship as well as the direction (positive vs. negative correlations).

## Creating a Correlation Matrix in Q

In Q, the correlation matrix is one of many built-in analytic functions. This particular function relies on an R library to calculate and create the correlation matrix. R is a powerful statistical analysis software and is integrated with Q.

To create a correlation matrix in Q, from the menus, select **Create > Correlation > Correlation Matrix**. In the **Report** **Tree **you will see an object labeled *correlation.matrix.*

With the *correlation.matrix* object in the **Report Tree** selected, the **Object Inspector** for the correlation matrix will appear to the right. This is where you provide all inputs and options for the correlation matrix.

## Data Preparation

In most cases, the variables supplied to the correlation matrix feature should be variables that belong to one or more **Number** or **Number - Multi** questions. This ensures that the analysis 'sees' the underlying numeric values in the data, rather than categories. Change the question type for the data via the **Question Type** drop down menu in the **Variables and Questions** tab. More on changing the **Question Type** is here. If you need to recode the data before calculating correlations, see How to Recode Numeric Data.

Input Options

There are several built-in input options for the Correlation Matrix as well as various output options.

**Input Type** – select *Variables*, *Questions* or *Table*.

**Variables:**When you select*Variables*as*Input Type*a drop-down menu will appear**;**select the*Variables*you want to use as inputs to the correlation matrix.**Questions:**When you select*Questions*as the*Input Type*a drop-down menu will appear**;**select the*Questions*to use as inputs to the correlation matrix. All variables included in a selected multi-variable Question will be used as inputs. You can select multiple questions.**Table:**When you select*Table*as the*Input Type*a drop down menu will appear**;**select a single Q Table to use as the correlation matrix input.

**Variable names: **when you select *Variables* as the *Input Type *a checkbox will appear**;** if checked, Q will display the variable *Name* instead of the variable *Label* in the correlation matrix output.

**Missing data** dictates how the function deals with missing input values. If set to:

*Error if missing**data*, the function will return an error if there are any missing input values.*Exclude cases**with missing data*the function will run but will exclude any cases where input variables have missing data.*Use partial data*(default option), the function will run with whatever values are present and will ignore any missing input values.

**Spearman correlations** – if checked, the correlation matrix function will calculate Spearman correlation instead of Pearson correlation which is the default. Use Spearman correlation if your input data is ordinal or continuous.

**Show cell values** – If set to *Yes*, Q will display the correlation coefficients in the matrix cells.

**Show row/column labels** –Shows or removes the labels.

## Generating the Correlation Matrix

Once you have selected all the input parameters, click the **Calculate** button at the top of the **Object Inspector** to run the correlation matrix function with the provided inputs. You can also check the **Automatic** checkbox (next to the **Calculate** button) which will cause the correlation matrix to be rerun whenever any of the inputs are changed.

Using a sample Technology MaxDiff survey data file, the following shows the Pearson correlations between various owned devices. Note that by default, Q will display the correlation matrix as a blue-red scale Heatmap.

A quick inspection of the results suggests that the correlations are reasonable as illustrated by the negative correlation between *Other mobile phone* ownership and *Nokia mobile phone* ownership. There is also a relatively high correlation between iPhone ownership with iPad and iPod ownership.

## Additional Properties

In Q, the correlation matrix function uses a library specifically designed to generate the Heatmap output. If, however, you prefer to have a table of correlation coefficients, you can create a separate R output and reference the *correlation.matrix* object coefficient values.

First, create an R output by selecting **Create > R Output**. To generate an R data frame (table) of the correlation coefficients, enter the following code into the **R CODE** section of the Object Inspector and click **Calculate**.

correlation.matrix$cor

From our technology example above, the following output is generated.

## Other correlations

Finally, tables of correlation coefficients can also be created in Q by selecting **Number** or **Number - Multi** questions in both the blue and brown drop-down menu on a table in the **Outputs** tab. This option has the advantage of being able to display correlations between two different questions.

**We hope you found this article helpful. Discover more about "Using Q"!**