Akaike’s Information Criterion, or AIC for short, is a commonly-used statistical measurement. In essence, it’s used to compare how statistical models compare in a qualitative standpoint. However, the AIC formula can be a little tricky to calculate. Fortunately, it’s much easier with spreadsheets. Let’s learn **how to calculate AIC in Microsoft Excel.**

## How to Calculate AIC in Excel

Calculating AIC in Excel is quite simple. All you need are a few inputs, derived from the statistical analysis that you have performed on a model of data. In fact, there are only two critical inputs used in the AIC formula:

**K.**This is the number of variables (called parameters) in your model, including the single intercept.**Log-likelihood.**This measures how well your model fits. Lower log-likelihood indicates a poor fit; higher log-likelihood implies a better fit.

The AIC formula itself reads as follows:

AIC = -2*Log-Likelihood + 2*K

Computing AIC in Excel, then, is quite straightforward. Excel doesn’t actually have a built-in AIC formula. But you can input the two variables (K and log-likelihood) into a pair of cells, and then construct a formula manually.

To do so, click into any empty cell in your workbook. In it, place your K value, the number of variables. In a second cell, place the log-likelihood that your statistical output derived. For this example, let’s use cells **A1** and **A2** for these two inputs.

Then, in a third cell, input the AIC formula:

=(-2*A2)+(2*A1)

When you’ve inputted your formula, hit **Enter** on your keyboard. Excel will return the result, in this case, **48.25. **

As you can see, it’s easy to calculate Akaike’s Information Criterion, or AIC, thanks to Microsoft Excel. This is another example of how spreadsheets make performing statistical calculations and analysis a breeze. You can craft and work with the formulas in seconds.