How to Create a Normal Distribution in Excel

What this does

NORM.DIST returns the probability that a normally distributed value falls at or below a point; NORM.INV takes a probability and returns the corresponding value. The cumulative argument is the one that catches people — TRUE gives the running probability you almost always want, FALSE gives the density curve height, which is only useful for plotting the bell shape. Their standardised siblings NORM.S.DIST and NORM.S.INV assume a mean of 0 and a standard deviation of 1, so they take z-scores directly. The assumption of normality is doing real work here and deserves a check before the numbers are trusted. Most people learn this as a sequence of clicks and forget it by next week; learning it as a pattern instead is what lets you apply it to the next, slightly different version of the problem without starting from scratch. That is the difference this page is trying to make. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “create a normal distribution 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 layout choice that keeps the sheet readable and sortable, but the practical win is that someone else can open the file and understand what happened without asking you.

A worked example

The share of deliveries arriving within 5 days when the mean is 4.2 and the deviation 1.8: =NORM.DIST(5, 4.2, 1.8, TRUE) returns about 0.67. The service level that 95 % of orders meet: =NORM.INV(0.95, 4.2, 1.8) returns roughly 7.2 days. Plotting the bell curve itself needs the density form with FALSE. These two turn a mean and a deviation into service levels and thresholds, which is what capacity and SLA planning actually asks for. 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. Here is the takeaway for “create a normal distribution in excel”: copy the answer if you are busy, but if you have a spare few minutes, rebuild the example in Excel yourself with the tool above open beside it. That single pass — type it, run it, watch the result move when you change an input — is what turns a formula you found into a technique you trust. Keep your inputs labelled and referenced, never hard-coded, and the same sheet stays correct and auditable as it grows. Done that way, you will not need to look this up again, and you will be the person others ask.

Common mistakes

• Passing FALSE for cumulative and reading the result as a probability; that is the density, not a probability.
• Applying it to visibly skewed data, where the normal assumption misstates the tails badly.
• A standard deviation of zero or negative, which returns #NUM!.

Frequently asked questions