The two values that define the confidence interval.

Two numbers based on a statistical sample that set upper and lower limits on a figure at a specified probability level. Example: If the 90-percent confidence limits on the mean of sampled tilt error are 1.4° and 2.0°, in repeated measurements under identical conditions the mean should fall within these limits 90% of the time.

The highest and lowest boundaries in a confidence interval. As used here, a confidence interval accounts for the possibility that different groups of individuals might have different risk estimates even if they have the same range of dose estimates. Because there is uncertainty in risk estimates that are made for different radiation dose levels, scientists often include a confidence interval with a risk estimate.

Two statistics that form the upper and lower bounds of a confidence interval.

the upper and lower values of a confidence interval. There is a percentage of confidence (typically 95%) that the true value of the parameter being estimated lies within the interval.

(Same as confidence interval, but is terminology used by Lauer and Asher.) "The range of scores or percentages within which a population percentage is likely to be found on variables that describe that population" (Lauer and Asher, 58). Confidence limits are expressed in a "plus or minus" fashion according to sample size, then corrected according to formulas based on variables connected to population size in relation to sample size and the relationship of the variable to the population size--the larger the sample, the smaller the variability or confidence limits.

(or intervals): These are probability limits, based on the data set and statistical model employed, that the "true value" lies within the limits specified. Typically limits are expressed at the 95% or 99% probability levels.

The limits of a confidence interval. These limits are computed from sample data and have a given probability that the unknown parameter is located between them.

Limits which bound a range of values which is believed, with a preassigned degree of probability, to include a specific value of a parameter or attribute.