INTERCEPT(array_y, array_x)

The INTERCEPT function returns the point where a "best fit" line meets the y-axis. This is calculated by applying a linear regression on the data points in array_x (the independent or controlled variable) and array_y (the dependent variable).

The formula used for intercept is:

image\ebx_-1027357371.gif

which is the same as:

AVG(array_y) - SLOPE(array_x, array_y) * AVG(array_x)

For example, suppose the following y-values were observed for the supplied x-values:

Y

4.7

6.0

11.2

10.6

8.2

7.3

15.8

11.7

X

1

2

3

4

5

6

7

8

A linear regression through these points would look like this:

image\ebx_345652550.gif

You calculate where the line crosses the y-axis using:

INTERCEPT({4.7, 6, 11.2, 10.6, 8.2, 7.3, 15.8, 11.7}, {1, 2, 3, 4, 5, 6, 7, 8})

which returns 4.942857.

See also:

FORECAST(x, array_y, array_x)

SLOPE(array_x, array_y)

STEYX(array_y, array_x)

Other statistical functions