In Excel: enable the Analysis ToolPak and use Data ▸ Data Analysis ▸ Regression, or get the same coefficients as a formula with LINEST.
On this page7
Enable the add-in once: File ▸ Options ▸ Add-ins ▸ Manage: Excel Add-ins ▸ Go ▸ tick Analysis ToolPak.
Arrange the outcome in one column and every predictor in adjacent columns with headers.
Data ▸ Data Analysis ▸ Regression; set the Y and X ranges, tick Labels, and choose an output location.
Read R Square for fit, then the p-value beside each coefficient to see which predictors are carrying the model.
For a live version that updates with the data, enter =LINEST(known_ys,known_xs,TRUE,TRUE) and read the coefficients from the first row.
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 “excel linear regression multiple variables” 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 visual that makes the number obvious at a glance 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. Check the referenced cells, argument order and result type in your workbook. Start with the worked example before changing an input, then compare the changed result with the calculation you expected. An error value or a result of a different type is a reason to inspect the inputs and arguments.
In Google Sheets
Google Sheets support for this task has not been verified. Check the function, arguments and workflow in the target product before transferring the example. Matching formula notation does not establish identical behaviour. The aim was to get you unstuck fast and leave you a little more capable than a copy-paste would. The answer is at the top and the detail above shows why it holds — so the next time a colleague asks, you can answer without reaching for search. For “excel linear regression multiple variables”, keep the input cells and the result visible while you check the formula in Excel. Follow the worked example and change one input at a time. The steps explain the workbook calculation; this page does not run a live calculator for that task.
Common mistakes
- Selecting non-adjacent predictor columns; both the ToolPak and
LINESTneed 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
Where is regression in Excel?
Data ▸ Data Analysis ▸ Regression, which appears only after the Analysis ToolPak add-in is enabled.
Is it available on a Mac?
Yes, the Analysis ToolPak ships with Excel for Mac 2016 and later and is enabled from Tools ▸ Excel Add-ins.
What does R squared tell me?
The share of the variation in the outcome the model accounts for. It always rises when predictors are added, so use Adjusted R Square to compare models of different size.
How do I get the equation without the report?
LINEST returns the coefficients and the intercept; SLOPE and INTERCEPT do the same for a single predictor.