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# Excel: How to Use Multiple Linear Regression for Predictive Analysis

Often you may want to use a multiple linear regression model youâ€™ve built in Excel to predict the response value of a new observation or data point.

Fortunately this is fairly easy to do and the following step-by-step example shows how to do so.

### Step 1: Create the Data

First, letâ€™s create a fake dataset to work with in Excel:

### Step 2: Fit a Multiple Linear Regression Model

Next, letâ€™s fit a multiple linear regression model using x1 and x2 as predictor variables and y as the response variable.

To do so, we can use the LINEST(y_values, x_values) function as follows:

Once we click enter, the regression coefficients appear:

The fitted multiple linear regression model is:

y = 17.1159 + 1.0183(x1) + 0.3963(x2)

### Step 3: Use the Model to Predict a New Value

Now suppose that weâ€™d like to use this regression model to predict the value of a new observation that has the following values for the predictor variables:

• x1: 8
• x2: 10

To do so, we can use the following formula in Excel:

Using these values for the predictor variables, the multiple linear regression model predicts that the value for y will beÂ 29.22561.

### Step 4: Use the Model to Predict Several New Values

If weâ€™d like to use the multiple linear regression model to predict the response value for several new observations, we can simply make absolute cell references to the regression coefficients: