The Excel NORMDIST function returns the normal (bell-curve) distribution for a given mean and standard deviation. It is a legacy function; Microsoft replaced it in Excel 2010 with NORM.DIST, which takes the same arguments.
Syntax
| Argument | Description | |
|---|---|---|
x | Required | The value at which to evaluate the distribution. |
mean | Required | The arithmetic mean of the distribution. |
standard_dev | Required | The standard deviation of the distribution (must be > 0). |
cumulative | Required | TRUE for the cumulative distribution (CDF); FALSE for the probability density (PDF). |
How to use it
NORMDIST evaluates the normal distribution at x. With cumulative = TRUE you get the probability that a value is at or below x; with FALSE you get the height of the bell curve at x.
The inverse, NORMINV (modern NORM.INV), turns a probability back into x. For the standard normal (mean 0, sd 1) you can use the shorter NORMSDIST.
Use NORM.DIST in Excel 2010 and later. NORMDIST still works for backward compatibility, but Microsoft recommends NORM.DIST, which has the same four arguments. New workbooks should use the modern name.
Try it: interactive demo
Pick a NORMDIST example to see the formula and its result.
Practice workbook
Frequently asked questions
Should I use NORMDIST or NORM.DIST?
NORM.DIST in Excel 2010 or later — it takes the same four arguments and is the supported version. NORMDIST is kept only so older workbooks keep working.What is the difference between the cumulative and density results?
cumulative = TRUE you get P(X ≤ x), the area under the curve up to x. With FALSE you get the density — the height of the bell curve at x.How does NORMDIST relate to NORMSDIST?
NORMSDIST is the special case where mean = 0 and standard deviation = 1 (the standard normal). =NORMDIST(x,0,1,TRUE) equals =NORMSDIST(x).Why does NORMDIST return an error?
standard_dev argument must be greater than 0, and all arguments must be numeric. A zero or negative standard deviation, or non-numeric input, produces an error.Master functions like this in one day
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