CONFIDENCE.NORM function

The CONFIDENCE.NORM function in Excel is used to calculate the confidence interval for a population mean, assuming a normal distribution. It returns the margin of error for the confidence interval, which you can then use to determine the upper and lower bounds of the interval.

Syntax:

CONFIDENCE.NORM(alpha, standard_dev, size)

Arguments:

• alpha: The significance level used to calculate the confidence level. For example, for a 95% confidence level, alpha would be 0.05 (since 1 – 0.95 = 0.05).
• standard_dev: The population standard deviation (the standard deviation of the sample data or an estimate if the population is not known).
• size: The size of the sample (the number of data points or observations).

How it works:

• The function uses the z-distribution (normal distribution) to calculate the margin of error for the confidence interval.
• The result tells you how much the sample mean can vary from the true population mean with a given confidence level.

Example:

If you have:

• A standard deviation of 10,
• A sample size of 100, and
• A confidence level of 95% (so alpha = 0.05),

You would use:

=CONFIDENCE.NORM(0.05, 10, 100)

This will return the margin of error for the confidence interval. To calculate the actual confidence interval for the sample mean, you would add and subtract the margin of error from the sample mean.

Interpreting the result:

• The output is the margin of error. If, for example, the result is 2.5, and your sample mean is 50, the confidence interval would be from 47.5 to 52.5, indicating that you can be 95% confident that the true population mean lies within this range.