A confidence interval is an interval in which a measurement or trial falls corresponding to a given probability. Usually, the confidence interval of interest is symmetrically placed around the mean, so a 50% confidence interval for a symmetric probability density function would be the interval such that
| (1) |
For a normal distribution, the probability that a measurement falls within standard deviations (
) of the mean
(i.e., within the interval
) is given by
| (2) | |||
| (3) |
Now let , so
. Then
| (4) | |||
| (5) | |||
| (6) |
where is the so-called erf function. The following table summarizes the probabilities
that measurements from a normal distribution fall within
for
with small values of
.
| 0.6826895 | |
| 0.9544997 | |
| 0.9973002 | |
| 0.9999366 | |
| 0.9999994 |
Conversely, to find the probability- confidence interval centered about the mean for a normal distribution in units of
, solve equation (5) for
to obtain
| (7) |
where is the inverse erf function. The following table then gives the values of
such that
is the probability-
confidence interval for a few representative values of
. These values can be returned by NormalCI[0, 1, ConfidenceLevel -> P] in the Wolfram Language package HypothesisTesting` .
| 0.800 | |
| 0.900 | |
| 0.950 | |
| 0.990 | |
| 0.995 | |
| 0.999 |