Linear Regression in Excel

Article byDhanamma Pandula
Reviewed byDheeraj Vaidya, CFA, FRM

Excel Linear Regression

Linear regression is a statistical tool in Excel used as a predictive analysis model to check the relationship between two sets of data or variables. We can estimate the relationship between two or more variables using this analysis. For example, we can see two variables: dependent and independent variables.

  • The dependent variable is the factor we are trying to estimate.
  • The independent variable is the factor that influences the dependent variable.

So, using Excel linear regression, we can see how the dependent variable goes through changes when the independent variable changes and helps us to decide which variable has a real impact mathematically.

Linear Regression Data Analysis Tool in Excel

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How to Add Linear Regression Data Analysis Tool in Excel?

Linear Regression in excel is available under analysis toolpakAnalysis ToolpakExcel's data analysis toolpak can be used by users to perform data analysis and other important calculations. It can be manually enabled from the addins section of the files tab by clicking on manage addins, and then checking analysis toolpak.read more, a hidden tool in Excel. We can find this under the “Data” tab.

You can download this Linear Regression Excel Template here – Linear Regression Excel Template

This tool is not visible until the user enables this. To enable this, follow the below steps.

  1. We must first go to the FILES >>Options.


    Linear Regression Excel Example 1

  2. Then, click on “Add-ins” under “Excel Options.”


    Linear Regression Excel Example 1-1

  3. Select “Excel Add-ins” under the “Manage” dropdown list in Excel and click on “Go.”


    Linear Regression Excel Example 1-2

  4. Check the box “Analysis ToolPak” in the “Add-Ins.”


    Linear Regression Excel Example 1-3

  5. Now, we should see the ” Data Analysis” option under the “Data” tab.


    Linear Regression Excel Example 1-4

With this option, we can conduct many “Data Analysis” options. Let us see some of the examples now.

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Examples

As we told you, linear regression Excel consists of two things: dependent and independent variables. For this example, we will use the below data of winter season jacket sold data with temperature in each month.

Linear Regression Excel Example 2

We have each month’s average temperature and jacket sold data. Here, we need to know which independent and dependent variables are.

Here “Temperature” is the independent variable because one cannot control the temperature, so this is the independent variable.

“Jackets Sold” is the dependent variable because the temperature increases and decreases in jacket sales.

Now, we will do the Excel linear regression analysis for this data.

  • Step 1: We must click on the “Data” tab and “Data Analysis.”
Linear Regression Excel Example 2-1
  • Step 2: Once we click on “Data Analysis,” we will see the below window. Scroll down and select “Regression” in excel.
Linear Regression Excel Example 2-2
  • Step 3: Select the “Regression” option and click on “OK” to open the window below.
Linear Regression Excel Example 2-3
  • Step 4: Here, the “Input Y Range” is the dependent variable, so in this case, our dependent variable is “Jackets Sold” data.
Linear Regression Excel Example 2-4
  • Step 5: The “Input X Range” is the independent variable, so in this case, our independent variable is “Temperature” data.
Linear Regression Excel Example 2-5
  • Step 6: Select the output range as one of the cells.
Linear Regression Excel Example 2-6
  • Step 7: To get the difference between the predicted and actual values, check the “Residuals” box.
Linear Regression Excel Example 2-7
  • Step 8: Click on the “OK.” We will have the below analysis.
Linear Regression Excel Example 2-8

The first part of the analysis is “Regression Statistics.”

Linear Regression Excel Example 2-9

Multiple R: This calculation refers to the correlation coefficient, which measures the strength of a linear relationshipLinear RelationshipA linear relationship describes the relation between two distinct variables - x and y - in the form of a straight line on a graph. When presenting a linear relationship through an equation, the value of y is derived through the value of x, reflecting their correlation.read more between two variables. The Correlation Coefficient is the value between -1 and 1.

  • 1 Indicates a strong positive relationship.
  • -1 indicates a strong negative relationship.
  • 0 indicates no relationship.

R Square: It is the coefficient of determinationCoefficient Of DeterminationCoefficient of determination, also known as R Squared determines the extent of the variance of the dependent variable which can be explained by the independent variable. Therefore, the higher the coefficient, the better the regression equation is, as it implies that the independent variable is chosen wisely.read more used to indicate the goodness of fit.

Adjusted R Square: This is the adjusted value for R SquareAdjusted Value For R SquareAdjusted R Squared refers to the statistical tool which helps the investors in measuring the extent of the variance of the variable which is dependent that can be explained with the independent variable and it considers the impact of only those independent variables which have an impact on the variation of the dependent variable.read more based on the number of independent variables in the data set.

Things to Remember

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This article is a guide to Linear Regression in Excel. We discuss linear regression data analysis in Excel, examples, and a downloadable Excel template. You may also look at these useful functions in Excel: –