Statistical
CONFIDENCE.NORM Function in Excel
Returns the confidence interval for a population mean using normal distribution.
Syntax
- =CONFIDENCE.NORM(alpha, standard_dev, size)
Arguments
- alpha (required): Significance level
- standard_dev (required): Population standard deviation
- size (required): Sample size
Examples
- =CONFIDENCE.NORM(0.05, 2.5, 50) - 95% confidence interval - Result: 0.693
CONFIDENCE.NORM for data analysis
- Confirm whether you need entire columns, filtered subsets, or distinct values.
- Use [COUNTIFS](/functions/countifs/) and [SUMIFS](/functions/sumifs/) for multi-criteria metrics.
- Pivot tables complement single-cell statistical formulas for exploration.
Common errors
- #NUM! if alpha <= 0 or >= 1
Use cases
- Confidence intervals
- Statistical inference
- Quality control
Frequently asked questions
- How do I calculate a 95% confidence interval? Use alpha=0.05 for 95% confidence: =CONFIDENCE.NORM(0.05, stdev, n). The result is the margin of error. CI = mean ± margin. So if mean=100 and margin=2.5, the 95% CI is 97.5 to 102.5.
- What is the difference between CONFIDENCE.NORM and CONFIDENCE.T? CONFIDENCE.NORM assumes you know the population standard deviation (rare). CONFIDENCE.T uses sample standard deviation and t-distribution, which is more appropriate for most real-world situations, especially with small samples (n<30).
- How does sample size affect confidence interval width? Larger samples give narrower intervals. The margin of error is proportional to 1/√n. Quadrupling sample size halves the margin of error. Use this to plan sample sizes: n = (z × stdev / desired_margin)².
Editorial review
- Reviewed by Excel.Directory Editorial Team. Updated May 2026.