How to Find Regression Equation in Excel

What this does

Regression fits a straight-line relationship between one outcome column and one or more predictor columns. The ToolPak produces a full report — coefficients, their standard errors, t statistics and p-values, R squared, and the F test for the model as a whole. LINEST returns the same numbers as a spilled array without the report layout. Both require the predictor columns to be contiguous. 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. Treat “find regression equation in excel” as a small repeatable workflow rather than a one-off click you hope to remember next time. Use a small test block before the live file, so any surprise in the affected cells shows up while it is still harmless. 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. That turns a data step that keeps your analysis trustworthy into a method you can reuse, explain, and defend when the workbook leaves your screen.

A worked example

Revenue in B2:B50 is modelled on ad spend in C and site visits in D. Data ▸ Data Analysis ▸ Regression with Input Y Range B1:B50, Input X Range C1:D50 and Labels ticked returns R Square 0.83, an ad-spend coefficient of 2.4 with a p-value of 0.004, and a visits coefficient whose p-value of 0.31 says it adds nothing once spend is in the model. The ToolPak output is the difference between an estimated relationship and a quantified one — the p-values are what stop a coincidence being presented as a driver. One habit worth forming early: name the cells that hold your inputs, so the formula reads in plain language instead of a string of cell addresses. A reviewer — or you in three months — can then follow the logic without decoding what B7 and D2 were supposed to mean, which is most of what makes a sheet maintainable.

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. Keep this page bookmarked for the next time the same question comes up. Better still, rebuild the example once in your own sheet — doing it yourself, with the tool above to check against, is what turns a copied formula into a technique you own. If you take one thing from this page on “find regression equation 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

• Selecting non-adjacent predictor columns; both the ToolPak and LINEST need one contiguous X block, so copy the columns together first.
• Reading LINEST's coefficients left to right in column order — it returns them in reverse, with the last predictor first.
• Reporting a high R squared as proof of causation when the predictors were chosen after seeing the data.
• Leaving strongly correlated predictors in the model, which makes individual coefficients unstable even when the fit looks excellent.

Frequently asked questions