Linear Regression in Excel (2022)

Excel Linear Regression

Linear Regression is a statistical tool in excel that is used as a predictive analysis model to check the relationship between two sets of data of variables. Using this analysis, we can estimate the relationship between two or more variables. We can see two kinds of variables, i.e., “Dependent Variable & Independent Variable.”

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

So, using excel Linear Regression, we can actually see how the dependent variable goes through changes when the independent variable changes and helps us to mathematically decide which variable has a real impact.

Table of contents
  • Excel Linear Regression
    • How to Add Linear Regression Data Analysis Tool in Excel?
    • Examples
    • Things to Remember
    • Recommended Articles
Linear Regression in Excel (1)

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How to Add Linear Regression Data Analysis Tool in Excel?

Linear Regression in excel is available under analysis 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 clickingon manage addins, andthen checkinganalysis more, which is a hidden tool in excel. This can be found under the Data tab.

Video: How to do a linear regression on excel

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. Go to FILE >>Options.

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    Video: Excel - Simple Linear Regression

  2. Click on “Add-ins” under “Excel Options”.

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  3. Select Excel Add-ins under Manage Drop Down List in excel and click on Go.

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

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

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With this option, we can conduct many “data analysis” options. Let’s see some of the examples now.

Video: How To Perform Simple Linear Regression In Excel


As I told, Linear Regression excel is consists of two things, i.e., “dependent & independent variables.” For this example, I am going to use the below data of winter season jacket sold data with temperature in each month.

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

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

Jackets Soldis the dependent variable because, based on the temperature increase and decreases jacket sale varies.

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

Video: Excel Basics - Linear Regression - Finding Slope & Y Intercept

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

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Multiple R: This calculation refers to the correlation coefficient, which measures the strength of a linear 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 more between two variables. The CorrelationCoefficient 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 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 more which is used to indicate the goodness of fit.

Adjusted R Square: This is the adjusted 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 more based on the number of independent variables in the data set.

Things to Remember

  • We can also use the LINEST function in excelread more.
  • You need to have a strong knowledge of statistics to interpret the data.
  • If the data analysis is not visible under the Data tab, we need to enable this option under the add-ins option.

Recommended Articles

This has been a guide to Linear Regression in Excel. Here we discuss How to do Linear regression data analysis in excel along with examples and a downloadable excel template. You may also look at these useful functions in excel –

Video: Excel 2016 Regression Analysis

  • Formula of Coefficient of Determination
  • Non-Linear Regression in Excel
  • Regression vs. ANOVA
  • Formula of Multiple Regression


How do you predict a value in a linear regression in Excel?

To add it in your workbook, follow these steps.
  1. Step 1 – Excel Options. Go to Files -> Options:
  2. Step 2 – Locate Analytics ToolPak. ...
  3. Step 3 – Add Analytics ToolPak. ...
  4. Step 1 – Select Regression. ...
  5. Step 2 – Select Options. ...
  6. Regression Statistics Table. ...
  7. ANOVA Table. ...
  8. Regression Coefficient Table.
Jun 22, 2020

Is Excel good for regression analysis?

Excel performs ordinary least squares regression. For more information, read my post about when to use regression analysis. To perform regression analysis in Excel, arrange your data so that each variable is in a column, as shown below. The independent variables must be next to each other.

How do I interpret multiple regression results in Excel?

Multiple Regression Interpretation in Excel - YouTube

How do you calculate linear regression?

The Linear Regression Equation

The equation has the form Y= a + bX, where Y is the dependent variable (that's the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-intercept.

What is regression equation in Excel?

(Linear) Regression Equation on Excel 2016 - YouTube

How do you interpret regression results?

The sign of a regression coefficient tells you whether there is a positive or negative correlation between each independent variable and the dependent variable. A positive coefficient indicates that as the value of the independent variable increases, the mean of the dependent variable also tends to increase.

How do you interpret regression analysis in Excel?

Excel Regression Analysis Output Explained - YouTube

How do you predict values in Excel?

Follow the steps below to use this feature.
  1. Select the data that contains timeline series and values.
  2. Go to Data > Forecast > Forecast Sheet.
  3. Choose a chart type (we recommend using a line or column chart).
  4. Pick an end date for forecasting.
  5. Click the Create.
Oct 15, 2018

What is a good R squared value?

In other fields, the standards for a good R-Squared reading can be much higher, such as 0.9 or above. In finance, an R-Squared above 0.7 would generally be seen as showing a high level of correlation, whereas a measure below 0.4 would show a low correlation.

What does a regression coefficient tell you?

In regression with a single independent variable, the coefficient tells you how much the dependent variable is expected to increase (if the coefficient is positive) or decrease (if the coefficient is negative) when that independent variable increases by one.

How do you interpret a linear regression equation?

A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and a is the intercept (the value of y when x = 0).


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