How to Find Correlation Coefficient in Excel

“find correlation coefficient in excel” comes up constantly, so this page leads with the exact answer, gives you a tool to try it on your own numbers, and only then explains the detail. Everything works in Excel on Windows and Mac and maps almost one-to-one to Google Sheets. Copy the answer above and get back to work, or read on to turn a one-off fix into something you never have to look up again.

Exact answer

In Excel: use =CORREL(array1, array2) — it returns a correlation coefficient from -1 to 1, where 0 means no linear relationship.

On this page8

Syntax

=CORREL(array1, array2)

Arguments

Argumentrequired / optionalDescription
array1requiredThe first set of values.
array2requiredThe second set, the same size as array1.

Related functions

SLOPE and INTERCEPTFORECASTVAR
ƒxCorrelation & TrendlineLive

6 pairs

Correlation (r)
0.9981

R² = 0.9962

Slope
1.9857

Intercept = 0.1667

=CORREL(A2:A10,B2:B10) · =SLOPE(B,A) · =RSQ()
Ctrl+CthenCtrl+Shift+V+Cthen+Ctrl+VPaste values · WindowsMac

What this does

CORREL measures how strongly two variables move together, on a scale from -1 (perfectly opposed) through 0 (unrelated) to 1 (perfectly aligned). It detects linear relationships only: a strong curved relationship can return a coefficient near zero, which is why plotting the data alongside the number is not optional. The other standing caveat is that correlation says nothing about cause. Both ranges must be the same size; pairs where either value is missing are dropped. The same idea underpins a lot of everyday Excel work, so the few minutes spent getting it right here pay back across every sheet you build afterwards. Treat it as a pattern, not a one-off, and it stops being something you look up and starts being something you reach for. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “find correlation coefficient in excel”. Start on a copy or a tiny sample, keep the affected cells 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 data step that keeps your analysis trustworthy, but the practical win is that someone else can open the file and understand what happened without asking you.

A worked example

Marketing spend in B2:B37 and revenue in C2:C37: =CORREL(B2:B37, C2:C37) returning 0.78 indicates a strong positive linear relationship. Squaring it gives R², the share of variance explained: =CORREL(B2:B37,C2:C37)^2 returns about 0.61, matching the R² a trendline reports. CORREL puts a single defensible number on "do these move together", which is the first question any two-variable analysis has to answer. 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

If you are in Google Sheets rather than Excel, the good news is that the formula shown here is identical and the workflow barely changes — menus sit across the top instead of in a ribbon, and a few function names differ slightly, but anything you build here moves across with little or no rework. Nothing on this page is behind a login: the tool runs entirely in your browser, the formula is shown in full with one-click copy, and the steps work the same on Windows and Mac. That is the whole promise here — the exact answer, a way to prove it on your own numbers, and just enough context to make it stick. If you take one thing from this page on “find correlation coefficient in excel”, make it the habit rather than the keystrokes: set the problem up with labelled inputs, reference those cells, and let Excel do the recomputing. Bookmark the page for the syntax, but do the example once in a blank sheet and check it against the tool above — five minutes of hands-on practice fixes the method in memory far better than re-reading, and it surfaces the small snags while they are still harmless. After that the technique is genuinely yours: faster than searching for it again, and reliable enough to drop into work that other people depend on.

Common mistakes

  • Reading correlation as causation, which the coefficient cannot support in either direction.
  • Trusting a near-zero result without plotting; CORREL is blind to non-linear relationships.
  • Ranges of different lengths, which returns #N/A.

Frequently asked questions

What counts as a strong correlation?

It depends entirely on the field. Above 0.7 is usually called strong in business data and would be weak in a physical measurement.

How do I get R-squared?

Square the coefficient: =CORREL(x,y)^2, or use =RSQ(y,x) directly. Both match the R² a chart trendline displays.

Does correlation prove causation?

No. It measures co-movement only; a lurking third variable explains a great many strong correlations.

Other ways people ask this

People reach this page typing “how to find the correlation coefficient on excel”, “how to find coefficient of variance in excel”, “find the correlation between 2 independent variables excel” and “finding correlation coefficient in excel”, among other phrasings; whichever wording you used, the fix above is the one you want.

Why do people search for this in so many different ways?

Because the same task has many names. “how to find the correlation coefficient on excel”, “how to find coefficient of variance in excel”, “find the correlation between 2 independent variables excel” all point at the one operation explained on this page, which is why they all lead here.