Standard deviation provides a measure of nearness between the sample mean and the true mean reliably for a large number of measurements. So, when there are limited measurements, how is the closeness of the true mean to random data or a sample mean estimated? A confidence interval is a statistically computed range of values around the mean, in which lies the true mean within a certain probability. The limits of this interval are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, standard deviation, and statistical factor –t–, which depends on the number of measurements and a desired confidence interval. As the measurements increase, the deviation from the mean becomes small, leading to a narrow confidence interval.