**Cubic regression** is a regression technique we can use when the relationship between a predictor variable and a response variable is non-linear.

The following step-by-step example shows how to fit a cubic regression model to a dataset in Excel.

**Step 1: Create the Data**

First, let’s create a fake dataset in Excel:

**Step 2: Perform Cubic Regression**

Next, we can use the following formula in Excel to fit a cubic regression model in Excel:

=LINEST(B2:B13, A2:A13^{1,2,3})

The following screenshot shows how to perform cubic regression for our particular example:

Using the coefficients in the output, we can write the following estimated regression model:

ŷ = -32.0118 + 9.832x – 0.3214x^{2} + 0.0033x^{3}

**Step 3: Visualize the Cubic Regression Model**

We can also create a scatterplot with the fitted regression line to visualize the cubic regression model.

First, highlight the data:

Then click the **Insert** tab along the top ribbon and click the first option within the **Insert Scatter (X, Y)** option in the **Charts** group. This will produce the following scatterplot:

Next, click the green plus sign in the top right corner of the chart and click the arrow to the right of **Trendline**. In the dropdown menu that appears, click **More Options**…

Next, click the **Polynomial** trendline option and select **3** for the order. Then check the box next to “Display Equation on chart”

The following trendline and equation will appear on the chart:

Notice that the equation in the chart matches the equation that we calculated using the **LINEST()** function.

**Additional Resources**

How to Perform Simple Linear Regression in Excel

How to Perform Multiple Linear Regression in Excel

How to Perform Polynomial Regression in Excel

Super and tgankz for your sharing

Your example does not work

you only show how to get the coefficient for the cubic term. How about showing the formula for the other two? Cells e1, f1 & g1.

Otherwise this page is not helpful