Guide to Computation of Excel CorrelationStep-by-step Guide
Microsoft Excel has many uses.
It is not limited to just computing sums of values but it can also be used to make key computations such as that of variances, otherwise known as a correlation coefficient.
This computation is used to inform companies to make important business decisions based on the effect of one company’s activity over another.
Defining Correlation
The relationship between two variables is referred to as Correlation.
When this is 0, it means that the changes in one activity or variable do not affect the other.
However, an increase or a decrease in coefficient indicates a non-constant effect with each other.
When the correlation coefficient is +1, an increase in variable X means an equal increase in variable Y.
This is also referred to as a perfect correlation.
However, when the correlation coefficient is -1, it means that an increase in variable X means an equal decrease in variable Y.
This is referred to as a perfect negative correlation.
Businesses value the result of the correlation coefficient because it aids them in making important business decisions.
For example, in checking whether or not social media campaigns result in more engagement from customers, businesses would be able to see the effect in terms of sales increase.
Otherwise, if the sale does not increase, it means the social media campaign does not have a direct effect on the sales.
Correlation Coefficient Computation
Here are the steps in computing Coefficient Correlation:
- Access Microsoft Excel.
- Install Analysis Toolpak.
- From the Top Bar Menu, click on Data.
- In the Upper Right-Hand Corner, select Data Analysis.
- Click on Correlation.
- Select the data range, and then the output.
- Make an Evaluation of the Correlation Coefficient.
Let’s delve into more detail with the steps stated above.
1. Access Microsoft Excel
As you open Microsoft Excel, begin by entering the different data points you need in a blank worksheet.
As shown in the example below, you can start typing them in Columns A and B.
2. Install Analysis Toolpak
If you do not have this installed yet, you can proceed by installing it.
Just go to File > Options > Add-ins.
Choose “Analysis Toolpak” and then click on OK.
If you are using a Mac computer, click on Insert > Get Add-ins.
If you do not see the Analysis Toolpak, type it in the search bar.
Click Add.
3. From the Top Bar Menu, click on Data
Once you have the Toolpak installed, you will see a list of options for your data analysis.
4. In the Upper Right-Hand Corner, select Data Analysis
When you click on Data Analysis, you will be able to see a list of analysis tools as shown below:
In your Mac, the analysis tools will be shown on the right side of the worksheet.
5. Click on Correlation
Click on Correlation and you will see the data range that you will have to fill in the details.
6. Select the data range, and then the output
Click on the Input Range and move your mouse to the cells you wish to be computed.
When you do this, it will automatically populate the box.
You may also choose to manually enter the information.
As for the output range, you can select on any empty cell.
Click OK.
7. Make an Evaluation of the Correlation Coefficient
As you can see below, you will find that Column 1 and Column 2 have neither a perfect nor perfect negative correlation.
As a matter of fact, any change in column 1 does not pose any impact on Column 2.
Correlation Matrix
The result of the correlation coefficient is also known as the Correlation Matrix.
When you have a perfect correlation or a perfect negative correlation, the results can be easily interpreted.
However, if we have the same example as the one above, the interpretation can be tricky.
For example, in studying whether or not the social media campaign has generated any positive impact on the sales of the company, we can safely conclude that the negative correlation indicates that it did not.
When you make it a regular habit of creating matrices, you will be in a better position to analyze the activities of the company and their impact on the business.
Correlation Coefficient Formula
If you are not using the Analysis Toolpak, you can choose to manually compute the correlation coefficient.
Here’s the formula:
If you are not that comfortable computing the matrix manually, it is always better to use the Analysis Toolpak.
The Correlation is not the Cause
What you must understand is that just because the result shows a perfect correlation or perfect negative correlation, it does not mean that the positive increase in the activity has directly caused a positive impact on the other activity.
The correlation coefficient may show the increase or decrease between two variables, but it does not mean that is the cause of such an increase or decrease.
Conclusion
It must be noted that the correlations do not tell the whole story and are just one part of the analysis that is helpful for strategy-making, financial analysis, sales, and marketing.
It can be used as a starting point for delving into further analysis to better aid companies in their decision-making process.