In Excel: use =CONFIDENCE.NORM(0.05, sd, n) — it returns the margin of error (the ± half-width) of a confidence interval around a mean, at a confidence level of 1 − alpha: alpha 0.05 gives 95 %, alpha 0.01 gives 99 %.
On this page8
Syntax
Arguments
| Argument | required / optional | Description |
|---|---|---|
alpha | required | Significance level — 0.05 for 95 % confidence. |
standard_dev | required | The population or sample standard deviation. |
size | required | The sample size. |
Related functions
n = 6 · mean = 14.67
Variance = 17.067
Need it as an auditable file?
Ships inside the linked template — formula-driven, unlocked, audit-ready.
What this does
CONFIDENCE returns the half-width of a confidence interval: the ± figure you place around a sample mean. The alpha argument is a significance level, not a confidence level, so 95 % confidence means passing 0.05 — the most common mistake with this function by a wide margin. CONFIDENCE.T uses the t-distribution and is the correct choice for small samples where the population deviation is unknown, which describes most real survey and test data. The result shrinks with the square root of the sample size, which is why quadrupling a sample only halves the error. 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. For “calculate confidence limits in excel”, 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 cells 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 calculation you can defend to a CFO or an auditor useful in real work: repeatable, auditable, and not dependent on memory or luck.
A worked example
A survey of 400 people with a mean of 7.2 and a deviation of 1.8: =CONFIDENCE.NORM(0.05, 1.8, 400) returns about 0.18, so the interval is 7.2 ± 0.18. Reporting it: ="7.2 ± " & ROUND(CONFIDENCE.NORM(0.05,1.8,400),2). For a sample of 25, =CONFIDENCE.T(0.05, 1.8, 25) is the honest choice and returns a noticeably wider figure. CONFIDENCE is what turns a sample mean into an honest claim, and the alpha-versus-confidence confusion is what makes it so often wrong. A practical tip before you scale it up: build it once on a small block of test data, confirm the number against the tool on this page, and only then point it at your real sheet. That one habit catches almost every mistake while it is still cheap to fix, long before a wrong figure reaches a report or a colleague.
In Google Sheets
Everything above works in Google Sheets too. Excel and Sheets share the formula syntax used here; only the surrounding menus are arranged differently. That portability is deliberate — learn it once and it follows you between the two tools and across Windows and Mac. 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. The short version of “calculate confidence limits in excel”: the answer is at the top of this page, the tool proves it on your own numbers, and the sections above explain why it holds so the next variation does not stump you. Excel rewards people who reference cells instead of typing values and who keep inputs separate from formulas, because that is what makes a result you can audit months later. Build it once, deliberately, with the live tool as a check, and you convert a one-off lookup into a reusable skill — which is the whole point of learning the why and not just the what.
Common mistakes
- Passing 0.95 instead of 0.05, which produces a nonsensically small margin.
- Using CONFIDENCE.NORM on a small sample where the t-distribution is correct and gives a wider, honest interval.
- Reporting a mean without an interval at all, which implies a precision the sample does not support.
Frequently asked questions
What alpha do I use for 95 % confidence?
0.05. Alpha is the significance level, which is 1 minus the confidence level.
CONFIDENCE.NORM or CONFIDENCE.T?
T for small samples with an unknown population deviation — which is most real data. NORM for large samples.
How do I halve my margin of error?
Quadruple the sample size. The margin shrinks with the square root of n.