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A confidence interval may be thought of as the range of probable true values for a
statistic. In general, as a population or
sample size increases, the confidence interval gets smaller. Estimates with smaller
confidence intervals are referred to as more "precise." Less precise estimates, such as
those calculated from small numbers, will
have wider confidence intervals.
Even for complete count datasets, such as birth and death certificate datasets, random
fluctuations over time will yield estimates that are not
reliable. For instance, the death rate for a short time period from a small population will not
reflect the true underlying death risk for that population.
The 95% confidence interval (calculated as 1.96 times the standard error of a statistic)
indicates the range of values within which the statistic would fall 95% of the time if
the researcher were to calculate the statistic from an infinite number of samples of
the same size drawn from the same base population.