Google Sheets provides functions for many data analysis methods, including linear regression. This method is frequently used to quantify the relationship between a dependent and an independent variable. In other words, if you’ve noticed a linear trend in your data, you can forecast future values using the linear regression method. The LINEST function in Google Sheets allows you to perform both simple and multiple linear regression on the known values for your variables. You can quickly find the slope and the intercept, as well as other regression statistics.

In this article, you will learn about the LINEST function and syntax, as well as how to use it for regression analysis in Google Sheets. You will see examples of how to use it when you have one explanatory variable - simple regression - and how to use it when you have multiple explanatory variables - multiple regression.

## LINEST Function Syntax

The LINEST function has four parameters, and only the first is required.

`=LINEST(known_data_y, [known_data_x], [calculate_b], [verbose])`
• known_data_y* (Required): The known values for the response or dependent variable (y).
• known_data_x (Optional): The known values for the explanatory or independent variable (x).
• calculate_b (Optional): Indicates whether the y-intercept (b) should be calculated. The default value is “TRUE”, which is what we want for linear regression.
• verbose (Optional): Indicates whether you would like to see additional regression statistics or just the slope and intercept. The default value is “FALSE”.

This means you can use it to calculate the trend in values for your dependent variable even if you don’t have an independent variable. However, you can also use it when you have multiple independent variables that need to be considered. This makes it a very flexible and useful function.

In the following sections, you will learn how to use the function for both simple and multiple linear regression. How To Perform What-If Analysis in Google Sheets

The What-If Analysis is a very important concept in financial modeling. Here’s how to perform a What-If Analysis in Google Sheets.

## Simple Linear Regression in Google Sheets

Follow the instructions below to run a simple linear regression analysis in Google Sheets. For this example, I will use the sales amount as the response or dependent variable. The explanatory or independent variable is the amount spent on paid advertising.

1. 1. Open the Google Sheets file with the data for the explanatory and response variables. Linear Regression in Google Sheets - Open Sheet with Simple Variables
1. 2. Type “=LINEST(“ in an empty cell and you will see the help pop-up. Select the array of cells with the known values for the response variable, “sales_amount”. Linear Regression in Google Sheets - Simple LINEST Known Y
1. 3. After the comma, select the range of known values for the independent variable, “paid_ads”. Linear Regression in Google Sheets - Simple LINEST Known X
1. 4. I will set the last two parameters to “TRUE”, as I want “b” to be calculated, and I want to see more regression statistics than the slope and intercept. Remember to close the parenthesis and press Enter. Linear Regression in Google Sheets - Simple LINEST Calculate B and Verbose
1. 5. That’s it. All the regression statistics are available in your spreadsheet, but which is which? In the next step, I include labels for each of the statistics provided. Linear Regression in Google Sheets - All Simple Regression Statistics
1. 6. Below, I have identified the statistics provided by the formula when the “verbose” parameter is “TRUE”. If the parameter is set to “FALSE” or left blank, only the “slope” and “intercept” statistics are provided. Linear Regression in Google Sheets - All Simple Regression Statistics with Labels

#### How to Find the Slope in Google Sheets

The SLOPE function is an important tool in financial analysis. Here’s how to find the slope in Google Sheets with a chart or by using the SLOPE function. ## Multiple Linear Regression in Google Sheets

Follow the instructions below to run multiple linear regression analysis in Google Sheets. I will build on the previous example by adding a second independent variable. The dependent variable is still the sales amount, but the explanatory variables are now the amount spent on paid advertising and the amount spent on sales salaries.

1. 1. Open the Google Sheets file with the data for the response variable and both explanatory variables. Linear Regression in Google Sheets - Open Sheet with Multiple Variables
1. 2. In an empty cell, type “=LINEST(“ and you will see the help pop-up. Select the array of cells with the known values for the response variable, “sales_amount”. Linear Regression in Google Sheets - Multiple LINEST Known Y
1. 3. After the comma, select the range of known values for the independent variables, “paid_ads” and “sales_salaries”. Linear Regression in Google Sheets - Multiple LINEST Known X
1. 4. The third parameter is set to “TRUE”, as I want “b” to be calculated. I also want to see all the regression statistics, so the last parameter is also “TRUE”. Remember to close the parenthesis and press “Enter”. Linear Regression in Google Sheets - Multiple LINEST Calculate B and Verbose
1. 5. That’s it. The statistics for the multiple regression are available in your spreadsheet. In the next step, I will identify the statistics with labels. Linear Regression in Google Sheets - All Multiple Regression Statistics
1. 6. Below, “s.error” is the standard error. The cells with “#N/A” can be ignored, as there is no error: the cells are simply not needed. Linear Regression in Google Sheets - All Multiple Regression Statistics with Labels

## Conclusion

As you have seen, linear regression analysis is easy using the LINEST function in Google Sheets. Whether you have one or multiple independent variables, you can quickly find the slope and the intercept.

However, you could also find those using the SLOPE and INTERCEPT functions. The difference is that LINEST can also provide a lot of additional regression statistics, which will allow you to perform a full analysis. These include standard errors for slope, intercept, and y-estimate, as well as the coefficient of determination, F statistic, degrees of freedom, and the regression and residual sums of squares.

You now know how to find simple and multiple linear regression in Google Sheets using the LINEST function. You also know how to identify the statistics represented by the function’s output, so you can quickly interpret the results. To learn more about performing data analysis in Google Sheets, check out our related article on How To Perform What-If Analysis in Google Sheets.