Statistical

INTERCEPT Formula

INTERCEPT returns the y-intercept of the linear regression line — the predicted value of y when x equals zero. Together with SLOPE, it defines the complete linear equation y = mx + b. Use it to establish baseline values, project starting points, or calculate fixed costs in a cost model.

Syntax

INTERCEPT(known_y, known_x)
ParameterDescription
known_y Parameter of the INTERCEPT function.
known_x Parameter of the INTERCEPT function.
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Examples

Fixed cost estimate

Formula
=INTERCEPT(C2:C20, B2:B20)
If C is total cost and B is production quantity, the intercept estimates fixed costs — the cost you'd have even with zero production.

Baseline metric

Formula
=INTERCEPT(D2:D13, A2:A13)
Returns the starting value (at x=0) of a trend line through monthly data. If A contains months 1-12, this is the estimated value at month 0.

Full regression equation

Formula
=INTERCEPT(Y, X) & " + " & SLOPE(Y, X) & "x"
Combines intercept and slope to display the regression equation as text, like '15000 + 2500x'.

Common Errors

#N/A

The known_y and known_x arrays have different lengths.

#DIV/0!

All x-values are the same (zero variance in x), making the regression line undefined.

Tips

May not be meaningful

The intercept assumes x=0 is a valid input. If your x-values range from 50 to 100, the intercept at x=0 is an extrapolation and may not make practical sense.

Argument order: y first, x second

Like SLOPE, the dependent variable (y) is the first argument. Swapping them gives a different and incorrect intercept.

Pair with FORECAST

Instead of manually computing SLOPE*x + INTERCEPT, use FORECAST(x, known_y, known_x) which does the same calculation in one step.

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