A simple linear regression line represents the line that best “fits” a dataset.

The following step-by-step example shows how to add a regression line to the following scatterplot in Google Sheets:

Let’s jump in!

**Step 1: Enter the Data**

First, let’s enter the values for the following dataset into Google Sheets:

**Step 2: Insert a Scatterplot**

Next, highlight the cell range **A2:B16**, then click the Insert tab along the top ribbon, then click **Chart**:

In the **Chart editor** panel, click **Chart type** and then scroll down and click **Scatter chart**:

The following scatterplot will appear:

**Step 3: Add a Regression Line**

Next, click the **Customize** tab within the **Chart editor** panel.

Then click the dropdown arrow next to **Series**, then scroll down and check the box next to **Trendline**.

Then click the dropdown arrow under **Label** and choose **Use Equation**:

A regression line will be added to the scatterplot and the equation of the regression line will be shown above the plot:

For this particular example, the regression line turns out to be:

**y = 0.911x + 4.65**

The way to interpret this is as follows:

- For each additional one unit increase in the
*x*variable, the average increase in the*y*variable is**0.911**. - When the
*x*variable is equal to zero, the average value for the*y*variable is**4.65**.

We can also use this equation to estimate the value of *y* based on the value of *x*.

For example, when *x* is equal to 15, the expected value for *y* is 18.315:

y = 0.911*(15) + 4.65= **18.315**

**Additional Resources**

The following tutorials explain how to perform other common tasks in Google Sheets:

How to Perform Logistic Regression in Google Sheets

How to Perform Polynomial Regression in Google Sheets

How to Calculate R-Squared in Google Sheets