## 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.

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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, which is a hidden tool in excel. This can be found under the Data tab.

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

**Go to FILE >>****Options.****Click on “****Add-ins**” under “Excel Options.”**Select “Excel Add-insExcel Add-insAdd-ins are different Excel extensions that can be found in the options section of the file tab. The first box displays the system's enabled add-ins, and if the user wishes to enable more, they must click on manage add-ins.read more” under Manage Drop Down List in excel and click on “Go.”****Check the box “****Analysis Toolpak**” in the “Add-Ins.”**Now we should see the “****Analysis Toolpak**” option under the “Data” tab.

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

### Examples

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.

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 Sold” **is 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.

**Step 1:**Click on the Data tab and Data Analysis.

**Step 2:**Once you click on “Data Analysis,” we will see the below window. Scroll down and select “Regression” in excel.

**Step 3:**Select the “Regression” option and click on “Ok” to open the below the window.

**Step 4:**“Input Y Range” is the dependent variable, so in this case, our dependent variable is**“Jackets Sold”**data.

**Step 5:**“Input X Range” is the independent variable, so in this case, our independent variable is**“Temperature”**data.

**Step 6:**Select the output range as one of the cells.

**Step 7:**To get the difference between the predicted values and actual values to check the box of “Residuals.”

**Step 8:**Click on the OK; we will have the below analysis.

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

**Multiple R: **This calculation refers to the correlation coefficient, which measures the strength of a linear relationship 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 which is 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

- We can also use the LINEST function in excelLINEST Function In ExcelThe built-in LINEST Function in Excel calculates statistics for a line by the least-squares regression method & returns an array that defines the line proving to be well-suited for the given data. read 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 –

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

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