In Excel: compute the mean and standard deviation, build a column of x values across the range, get the height of the curve with =NORM.DIST(x, mean, sd, FALSE), then plot x against that column as a Scatter with Smooth Lines.
On this page7
Compute the mean with =AVERAGE(range) and the standard deviation with =STDEV.S(range) into two cells.
Build an x column starting at mean − 3×sd and stepping evenly to mean + 3×sd; 50 to 100 points is plenty.
Beside it compute =NORM.DIST(x, $mean, $sd, FALSE) — the FALSE is what gives the bell rather than the S-curve.
Select both columns and choose Insert ▸ Scatter ▸ Scatter with Smooth Lines.
To overlay the real data, add a histogram of the values as a second series on a secondary axis, since counts and densities use different scales.
Anchor the mean and sd cells with $ so the NORM.DIST formula fills down cleanly.
What this does
A bell curve is the plot of the normal distribution defined by your data's mean and standard deviation. Excel has no "insert bell curve" button, so you build it: AVERAGE and STDEV.S give the two parameters, a column of evenly spaced x values spans roughly mean ± 3 standard deviations, and NORM.DIST with its last argument set to FALSE returns the probability density — the curve's height — at each x. Setting that argument to TRUE instead gives the cumulative S-curve. Plotting the result needs Scatter with Smooth Lines; a line chart treats the x values as categories and distorts the shape. 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 “normal distribution graph 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 chart 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
200 test scores in A2:A201. D1 = =AVERAGE(A2:A201) → 72.4, D2 = =STDEV.S(A2:A201) → 11.8. In F2 put =$D$1-3*$D$2 and in F3 =F2+($D$2*6/60), filled down to F62 — 61 points spanning ±3σ. In G2: =NORM.DIST(F2, $D$1, $D$2, FALSE), filled down. Select F2:G62 and Insert ▸ Scatter ▸ Scatter with Smooth Lines. The peak sits at 72.4 and the curve is near zero by 37 and 108. A bell curve is how a set of measurements gets turned into a statement about how likely a value is — grading, quality limits and process control all start with the mean, the standard deviation and this shape. 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 “normal distribution graph excel”, 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
- Using a Line chart instead of a Scatter chart, which spaces the x values evenly by position and misshapes the curve.
- Passing TRUE as the fourth
NORM.DISTargument, which draws the cumulative distribution rather than the bell. - Using STDEV.P on a sample; STDEV.S is the right choice unless the data really is the whole population.
- Plotting a bell curve over data that is visibly skewed or bimodal, which asserts a normality the data does not have.
- Leaving the x values unsorted, which makes the smooth line double back on itself.
Frequently asked questions
How do I make a bell curve in Excel?
Compute the mean and standard deviation, build a column of x values across mean ± 3 standard deviations, calculate =NORM.DIST(x, mean, sd, FALSE) beside it, and plot the two columns as a Scatter with Smooth Lines.
What does the FALSE argument do in NORM.DIST?
It asks for the probability density — the height of the bell at that x. TRUE returns the cumulative probability instead, which draws an S-shaped curve.
How do I overlay my actual data?
Add a histogram of the raw values as a second series and put it on a secondary axis. Counts and probability densities are not on the same scale, so one axis would flatten the curve.
How wide should the x range be?
Mean ± 3 standard deviations covers about 99.7% of a normal distribution, which is enough for the curve to reach the baseline at both ends.