Performing a simple linear regression in Excel

When teaching cost behavior in a managerial or cost accounting course, we explain that there are various methods a company can use to estimate its fixed and variable costs, including regression analysis. The next time you cover this topic, consider teaching students how to perform a simple linear regression analysis in Excel.  Below is an example screenshot illustrating 12 months of cost data for a restaurant.  

To perform a simple linear regression to estimate the restaurant’s fixed and variable costs, perform the following steps.  

Step 1: Click on the Data tab, and then click Data Analysis (in the Analysis group). (Note: If you don’t have the Data Analysis option, you will need to install the Analysis ToolPak add-in. See our previous article on how to do this.)

Step 2: Select Regression and then click OK.

Step 3: In the Regression dialog box that pops up, you must identify your Y variable, which is the dependent variable. In this example the dependent variable is the “total costs” column. Select the data in this column.

Step 4: You must also identify your X variable, which is your independent variable. In this example the independent variable is the “# of meals” column. Select the data in this column, then click OK. 

The default option is for the regression results to be inserted into a new worksheet. You will see the results in a different place if you have selected a different output option. We chose to have the regression results inserted into Sheet2 of our workbook, and the results are below:  

Now that you have the regression results, you can discuss with the students the key pieces of information being displayed, including the coefficients (the intercept representing the fixed costs, and the X variable 1 representing the variable costs) and how to interpret the R square and adjusted R square values.

The next time you teach cost behavior, consider expanding your students’ Excel skills by teaching them how to perform a simple linear regression, one of the many options within the Data Analysis function.

— Wendy Tietz, CPA, CGMA, Ph.D., is a professor of accounting at Kent State University in Kent. Ohio; Jennifer Cainas, CPA, DBA, is a clinical professor at the University of South Florida in Tampa; and Tracie Miller-Nobles, CPA, is an associate professor of accounting at Austin Community College in Austin, Texas. See their site AccountingIsAnalytics.com for resources they have developed for teaching data analytics in introductory accounting. To comment on this article or to suggest an idea for another article, contact senior editor Courtney Vien at Courtney.Vien@aicpa-cima.com.