Excel INTERCEPT Function

There are two ways to “excel intercept function”: the quick way you copy and the durable way you understand. This page gives you both. The exact Excel answer is above; below, we build the small mental model that makes the fix stick, so the next variation of the same problem solves itself.

Exact answer

In Excel: use =SLOPE(known_ys, known_xs) and =INTERCEPT(known_ys, known_xs) — together they give the two coefficients of the best-fit straight line, y = slope × x + intercept.

On this page8

Syntax

=SLOPE(known_ys, known_xs) and =INTERCEPT(known_ys, known_xs)

Arguments

Argumentrequired / optionalDescription
known_ysrequiredThe dependent values — the thing being predicted.
known_xsrequiredThe independent values, the same size as known_ys.

Related functions

FORECASTCORRELTREND
Annotated stepsExcel
1

Select a cell for the slope and type =SLOPE(.

2

Select the y values (the outcome) FIRST, then a comma, then the x values.

3

Repeat in a second cell with =INTERCEPT and the same argument order.

4

Combine them as intercept + slope × x to predict any new value.

Ctrl+CthenCtrl+Shift+V+Cthen+Ctrl+VPaste values · WindowsMac

Need it as an auditable file?

Ships inside the linked template — formula-driven, unlocked, audit-ready.

View template

What this does

SLOPE and INTERCEPT return the two numbers that define the least-squares regression line through a set of points. SLOPE is the rate of change — how much y moves per unit of x — and INTERCEPT is where the line crosses at x = 0. Written out they reproduce exactly the trendline equation a chart displays, which makes them the way to use a fitted line in calculations rather than merely look at one. Watch the argument order: the y values come first, which is the reverse of how most people say "x against y". Most people learn this as a sequence of clicks and forget it by next week; learning it as a pattern instead is what lets you apply it to the next, slightly different version of the problem without starting from scratch. That is the difference this page is trying to make. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “excel intercept function”. Start on a copy or a tiny sample, keep the affected formula visible, and compare the result with the tool above before you touch the real workbook. When a formula is involved, keep the inputs labelled beside it, reference cells instead of typing values, and apply number formatting only after the result checks out. The point is a calculation you can defend to a CFO or an auditor, but the practical win is that someone else can open the file and understand what happened without asking you.

A worked example

Units produced in B2:B40 and total cost in C2:C40: =SLOPE(C2:C40, B2:B40) returns the variable cost per unit and =INTERCEPT(C2:C40, B2:B40) the fixed cost. Predicting the cost of 250 units is then =INTERCEPT(...) + SLOPE(...)*250, which is what FORECAST.LINEAR does in a single call. SLOPE and INTERCEPT take a chart trendline out of the picture and put it into the model, where it can drive actual calculations. A practical tip before you scale it up: build it once on a small block of test data, confirm the number against the tool on this page, and only then point it at your real sheet. That one habit catches almost every mistake while it is still cheap to fix, long before a wrong figure reaches a report or a colleague.

In Google Sheets

Google Sheets handles this almost identically to Excel. The formula syntax above is the same, and the menu lives under a slightly different label rather than a ribbon tab. Use the platform toggle at the top of the page to switch every keyboard shortcut between Windows and Mac, and expect at most cosmetic differences in naming. Nothing on this page is behind a login or a download: the exact answer is at the top, and the detail below it is there for when you need it. That is the whole promise here — the answer first, and just enough context to make it stick. Here is the takeaway for “excel intercept function”: copy the answer if you are busy, but if you have a spare few minutes, rebuild the example in Excel yourself with the tool above open beside it. That single pass — type it, run it, watch the result move when you change an input — is what turns a formula you found into a technique you trust. Keep your inputs labelled and referenced, never hard-coded, and the same sheet stays correct and auditable as it grows. Done that way, you will not need to look this up again, and you will be the person others ask.

Common mistakes

  • Reversing the arguments — y comes first in both functions, and swapping them silently returns a different line.
  • Extrapolating far beyond the observed x range, where a straight line has no support from the data.
  • Fitting a line to plainly curved data; check the scatter plot before trusting either coefficient.

Frequently asked questions

Which argument comes first?

The y values — the thing being predicted. =SLOPE(known_ys, known_xs).

How do I get the trendline equation from a chart into cells?

SLOPE and INTERCEPT return exactly those two coefficients, so you can use the fitted line in formulas instead of reading it off the chart.

How do I predict a value?

=INTERCEPT(ys,xs) + SLOPE(ys,xs)*newX, or the shorter =FORECAST.LINEAR(newX, ys, xs).