Excel like a finance pro.
Statistical function
STEYX
Returns the standard error of the predicted y for each x in a regression.
When to use it
The standard error of the regression: the typical size of the residuals around the fitted line, in y units.
The shape of it
- Syntax
=STEYX(known_y's, known_x's)
Worked examples
The shared dataset
=STEYX({2,4,6,9},{1,2,3,4}) → 0.387298335
Residuals 0.2, -0.1, -0.4, 0.3; sum of squares 0.3 over n-2.
Forecast error
=STEYX(B2:B13,A2:A13) → 2,150
Typical forecast error of the sales-on-spend line.
Prediction band
=FORECAST.LINEAR(20000,B2:B13,A2:A13)±2*STEYX(B2:B13,A2:A13) → 49,400 ± 4,300
A rough 95% prediction band.
Worth knowing
- The same number LINEST reports in row 3, column 2.
- Compare with STDEV.S of y: a much smaller STEYX means the line explains a lot.
- Needs at least three points.
Where it goes wrong
- #DIV/0! with fewer than three points.
- #N/A when the arrays differ in size.
Related
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