The STEYX function calculates the standard error associated with a linear regression on the data points described by array_y (the dependent variable) and array_x (the independent or controlled variable) according to the formula:
Standard error is a measure of the amount of error associated with a prediction of y given 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:
Suppose you want to forecast y for x = 10 and supply a standard error with this forecast. The standard error would be calculated using:
STEYX({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 2.84.
See also: