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.
Mean = 70.714 · Std deviation = 5.992
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. Keep the inputs visible and clearly labelled and the whole thing stays auditable — anyone who opens the file later, including you, can see at a glance exactly what feeds the result and change one assumption without hunting through the formula. For “excel bell curve chart”, the reliable version is a short checking loop, not just the first command that appears to work. Run it on a deliberately small range first, watch how the affected chart change, and only then apply the same setup to the full sheet. 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 is what makes a visual that makes the number obvious at a glance useful in real work: repeatable, auditable, and not dependent on memory or luck.
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. 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. 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, the tool proves it, and the detail above shows why it holds — so the next time a colleague asks, you can answer without reaching for search. Treat “excel bell curve chart” as a small building block rather than a chore. Once the inputs sit in their own cells and the formula reads from them, the same setup answers a dozen related questions with a tweak, and Excel keeps every dependent figure current as the data changes. The tool above is there so you can rehearse and verify before committing anything to a real workbook; the steps and worked example are there so the logic sticks. Get it right once and it stops costing you time — it starts saving it, every time the question comes back around.
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.