# LINEST Function in☝️ Google Sheets Explained (Definition, Syntax, How to Use It, Examples)

This guide covers everything you need to know about the Google Sheets LINEST function, including its definition, syntax, use cases, and how to use it.

Quick Jump

## What is the LINEST Function? How Does It Work?

The LINEST function in Google Sheets helps you understand the straight-line trend in a set of data, which is great for making predictions in areas like finance or sales. It uses a math technique called “least squares” to find the best-fitting straight line through your data points.

Here’s how it works: LINEST takes two main inputs, known_data_y and known_data_x. The ‘known_data_y’ is a list of outcomes you already have (these are your ‘y’ values), and ‘known_data_x’ is a list of the conditions or factors related to those outcomes (these are your ‘x’ values).

If you’re looking at more than one factor, LINEST can handle that, too. Just make sure each row in ‘known_data_x’ represents a different factor if ‘known_data_y’ is a single row, or each column if ‘known_data_y’ is a single column.

Be aware that if you’re looking at multiple factors, LINEST gives you the results in reverse order of the input. So, the first result relates to the last factor you entered, and so on.

You can also tweak the LINEST function to get more detailed stats or to set the constant value to zero, making it a pretty flexible tool.

Finally, it’s important that your ‘known_data_x’ and ‘known_data_y’ lists are the same length. If they’re not, LINEST will give you an error message filled with #N/A values.

## LINEST Syntax

The syntax and arguments for the function are as follows:

LINEST(known_data_y, [known_data_x], [calculate_b], [verbose])

This function has four arguments, two of which are optional:

• known_data_y: This is the array or range containing the dependent (y) values that are already known. These values are used to curve fit an ideal linear trend.
• known_data_x (optional): This represents the values of the independent variable(s) corresponding with known_data_y. If known_data_y is a one-dimensional array or range, known_data_x may represent multiple independent variables in a two-dimensional array or range. For example, if known_data_y is a single row, each row in known_data_x is interpreted as a separated independent value, and similarly if known_data_y is a single column. Please note that for multiple independent variables, the order of the output parameters corresponds to the input variables in reverse.
• calculate_b (optional): This is a logical value that, if TRUE, forces the constant term to be 1. If FALSE, the constant term is calculated normally. If omitted, it is set to TRUE by default.
• verbose (optional): This is a logical value that, if TRUE, returns additional regression statistics. If FALSE or omitted, only the slope and y-intercept are returned.

Usage notes related to syntax and arguments:

• The known_data_y argument is required. If it is omitted, the function will return an error.
• The known_data_x argument is optional. If it is omitted, the function will use a default array {1,2,3,…} with the same length as known_data_y.
• The calculate_b and verbose arguments are optional. If they are omitted, they are set to TRUE by default.
• The known_data_y and known_data_x arguments must be arrays or ranges of the same size. If they are not, the function will return an error.
• If known_data_y is a one-dimensional array or range, known_data_x may represent multiple independent variables in a two-dimensional array or range.
• For multiple independent variables, the order of the output parameters corresponds to the input variables in reverse.

## Examples of How to Use the LINEST Function

Here are some practical examples of how to use the LINEST function in Google Sheets:

### Example #1: Simple Linear Regression

First, let’s say you have some data in cells A1:A10 for ‘x’ values and B1:B10 for ‘y’ values, and you want to find the slope and intercept of the line that best fits this data.

To find the slope, click on an empty cell and enter this formula: =INDEX(LINEST(B1:B10,A1:A10),1,1)

The result in the cell will be the slope of the line that best fits your data.

### Example #2: Multiple Linear Regression

In this example, you have a dataset spread across cells A1:C10 and want to analyze multiple variables against an outcome found in cells D1:D10.

For the coefficient of the first independent variable, click on an empty cell and type: =INDEX(LINEST(D1:D10,A1:C10,TRUE,TRUE),1,1)

The result will display the coefficient related to the first independent variable in your dataset. You can find coefficients for other variables by tweaking the index number in the formula.

### Example #3: Calculating the Standard Error

If you want to calculate the standard error of the estimate, you can use the LINEST function as follows:

1. Click on a cell where you want the standard error to appear.
2. Type the following formula: =INDEX(LINEST(B1:B10,A1:A10,TRUE,TRUE),2,1) and press Enter.
3. The standard error of the estimate will appear in the cell.

### Example #4: Calculating the R-squared Value

If you’re interested in finding the standard error for your simple linear regression model, this is how you can do it.

Click on a cell where you’d like to see the standard error and enter this formula: =INDEX(LINEST(B1:B10,A1:A10,TRUE,TRUE),2,1)

The result will show the standard error of your estimated line, giving you an idea of how accurately the line represents your data points.

## Why Is LINEST Not Working? Troubleshooting Common Errors

If you’re experiencing problems with the LINEST function in Google Sheets, several common errors may be the cause. Understanding these errors, their causes, and their solutions will help you quickly troubleshoot and resolve the issue.

### #VALUE! Error

Cause: This error typically occurs when one of the function’s arguments or inputs is invalid. Examples include non-numerical values, non-contiguous arrays, or cells that contain text instead of numbers.

Solution: Double-check your input data. Ensure that all data ranges are numerical, contiguous, and do not contain any text. You should also ensure that your data ranges match in size. For instance, if your known-y’s range has five values, your known-x’s range should also have five values.

### #REF! Error

Cause: A #REF! error signifies that the function refers to a cell that’s not valid. This can occur if you’ve deleted cells or columns that are being used by the function.

Solution: Review the cells your formula is referencing. If any have been deleted, you’ll need to either undo the deletion or adjust your formula to reference the correct cells. Make sure that all cell references in your formula are valid.

### #N/A Error

Cause: The #N/A error usually means the function’s calculations failed. This can occur if your known-x range has fewer than two rows or your data arrays are of different sizes.

Solution: Ensure that your known-x’s range has at least two rows of data and that your known-y’s and known-x’s ranges match in size. If the problem persists, you may need to adjust your data to ensure it is suitable for regression analysis.

### #NUM! Error

Cause: The #NUM! error usually occurs when the function can’t calculate a result because the input data is unsuitable. For instance, you’ll see this error if all the values in your known-x’s range are identical because it is impossible to calculate a linear trend for a single value.

Solution: Review your input data to ensure it is suitable for linear regression. You may need to adjust your data or use a different function if your known-x’s range only contains identical values.

For more details on the LINEST function, check out the official documentation at the Google Docs Editors Help Center.