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> For a complete documentation index, see https://help.sigmacomputing.com/docs/regressionintercept/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://help.sigmacomputing.com/_mcp/server.

# RegressionIntercept

> Use the Sigma RegressionIntercept function to calculate the y-intercept of the linear regression line.

> **Info**
>
> This function isn't compatible with all data platform connections. To check if your connection supports it, see [Supported data platforms and feature compatibility](/docs/region-warehouse-and-feature-support#supported-data-platforms-and-feature-compatibility).

The **RegressionIntercept** function calculates the y-intercept of the linear regression line. This provides you with the predicted value of a variable when the other variable is equal to zero.

> **Info**
>
> The **RegressionIntercept** function is an aggregate function.
>
> Aggregate functions evaluate one or more rows of data and return a single value.
>
> In a table element, the aggregate is calculated for each grouping. For information on how to add a grouping with an aggregate calculation to a table, see [Group columns in a table](/docs/create-and-manage-tables#group-columns-in-a-table).
>
> In a table with no groupings, the aggregate is calculated for each row. For information on how to calculate summary statistics across all rows in a table, see [Add summary statistics to a table](/docs/create-and-manage-tables#add-summary-statistics-to-a-table).
>
> To learn more about using aggregate functions, see [Building complex formulas with grouped data](https://www.sigmacomputing.com/resources/training-videos/table-grouping-and-functions#complex-formulas).

## Syntax

```sigma
RegressionIntercept(y, x)
```

### Function arguments

|       |                                                                           |
| :---- | :------------------------------------------------------------------------ |
| **y** | The dependent variable, expected to change as a result of changes in `x`. |
| **x** | The independent variable.                                                 |

## Notes

* The function returns null if the arguments used provide only a single data point.

## Example

A table contains an *AdSpend* column (tracking monthly advertising spend) and a *Revenue* column (tracking month revenue). You can use the **RegressionIntercept** function to find what the baseline monthly revenue is when the monthly advertising spend is zero.

```sigma
RegressionIntercept([Revenue], [AdSpend])
```

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