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:
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:
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: