# INTERCEPT

Calculates the point at which a line will intersect the y-axis by using existing x-values and y-values. The intercept point is based on a best-fit regression line plotted through the known x-values and known y-values. Use the intercept when you want to determine the value of the dependent variable when the independent variable is 0 (zero). For example, you can use the INTERCEPT function to predict a metal's electrical resistance at 0°C when your data points were taken at room temperature and higher.

**Syntax**

**INTERCEPT**(**known_y's**,**known_x's**)

**Known_y's** is the dependent set of observations or data.

**Known_x's** is the independent set of observations or data.

**Remarks**

- The arguments should be either numbers or names, arrays, or references that contain numbers.
- If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with the value zero are included.
- If known_y's and known_x's contain a different number of data points or contain no data points, INTERCEPT returns the #N/A error value.
- The equation for the intercept of the regression line is:
where the slope is calculated as:

**Example**

`INTERCEPT({2, 3, 9, 1, 8}, {6, 5, 11, 7, 5})`

equals 0.0483871