# regr_intercept()

Uses two numerical fields to calculate a trend line, then returns the y-intercept value. Use this function to find out the likely value of *field_y* when *field_x* is zero.

```nolang
regr_intercept(field_y, field_x)
```

*field_y* is a grouped dependent numeric expression and *field_x* is a grouped independent numeric expression. `regr_intercept(field_y, field_x)` uses simple linear regression to calculate the trend line. The input fields (*field_y*, *field_x*) must contain at least two pairs of non-null values. This function works with simple grouped values but not with cogroups.

## Example - What Is the Likely Amount Won If the Number of Activities Is Zero?

Suppose that you have a dataset that includes the number of activities (such as meetings) and the won opportunity amount.

![Sample scatter plot.](https://a.sfdcstatic.com/developer-website/sfdocs/analytics/media/bi_dev_guide_saql/bi_saql_fn_agg_regint.png)

What size of deal can you expect to win if you don't have any activities with an account? `regr_intercept` performs a linear analysis on your data then calculates the y-intercept (that is, the value of Amount Won when Number of Activities is zero).

```nolang
q = load "Data";
q = group q by all;

--trunc() truncates the result to two decimal places
q = foreach q generate trunc(regr_intercept('Amount', 'NumActivities'),2) as intercept;
```

The projected deal size with no activities is $15.04 million dollars.

![Diagram showing y intercept of a regression line.](https://a.sfdcstatic.com/developer-website/sfdocs/analytics/media/bi_dev_guide_saql/bi_saql_fn_agg_y_int.png)

**See Also**

- [regr_slope()](/docs/analytics/bi-dev-guide-saql/guide/bi-saql-fn-agg-rs.md)