You can use the **LINEST** function to quickly find a regression equation in Excel.

This function uses the following basic syntax:

LINEST(known_y's, known_x's)

where:

**known_y’s**: A column of values for the response variable**known_x’s**: One or more columns of values for the predictor variables

The following examples show how to use this function to find a regression equation for a simple linear regression model and a multiple linear regression model.

**Example 1: Find Equation for Simple Linear Regression**

Suppose we have the following dataset that contains one predictor variable (x) and one response variable (y):

We can type the following formula into cell **D1** to calculate the simple linear regression equation for this dataset:

=LINEST(A2:A15, B2:B15)

Once we press **ENTER**, the coefficients for the simple linear regression model will be shown:

Here’s how to interpret the output:

- The coefficient for the intercept is
**3.115589** - The coefficient for the slope is
**0.479072**

Using these values, we can write the equation for this simple regression model:

**y = 3.115589 + 0.478072(x)**

**Note**: To find the p-values for the coefficients, the r-squared value of the model, and other metrics, you should use the Regression function from the Data Analysis ToolPak. This tutorial explains how to do so.

**Example 2: Find Equation for Multiple Linear Regression**

Suppose we have the following dataset that contains two predictor variables (x1 and x2) and one response variable (y):

We can type the following formula into cell **E1** to calculate the multiple linear regression equation for this dataset:

=LINEST(A2:A15, B2:C15)

Once we press **ENTER**, the coefficients for the multiple linear regression model will be shown:

Here’s how to interpret the output:

- The coefficient for the intercept is
**1.471205** - The coefficient for x1 is
**0.047243** - The coefficient for x2 is
**0.406344**

Using these values, we can write the equation for this multiple regression model:

**y = 1.471205 + 0.047243(x1) + 0.406344(x2)**

**Note**: To find the p-values for the coefficients, the r-squared value of the model, and other metrics for a multiple linear regression model in Excel, you should use the Regression function from the Data Analysis ToolPak. This tutorial explains how to do so.

**Additional Resources**

The following tutorials provide additional information on regression in Excel:

How to Interpret Regression Output in Excel

How to Add a Regression Line to a Scatterplot in Excel

How to Perform Polynomial Regression in Excel

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