# confidence interval

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## confidence interval

n. Statistics
A range of values that contains with a specified probability the true value of a given parameter.

## confidence interval

n
(Statistics) statistics an interval of values bounded by confidence limits within which the true value of a population parameter is stated to lie with a specified probability
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(3) is a point estimation, which is calculated by using experimental data in order to determine whether the additive model is adequate or not, the confidence limits for the prediction error must be evaluated .
Conservative management had a high success rate, with 75% (n= 174/232; 95% confidence limits [CL]: 69%, 80%) of all birds successfully released back to the wild.
In 2011, almost 69,000 cases showed an aggregate amount of about \$2.7 billion over the upper confidence limits. On average, this is an amount of about \$39,000 per discharge.
[Q.sub.[alpha]] and [T.sup.2.sub.[alpha]] are confidence limits for Q and [T.sup.2] statistics, respectively.
Table 1: Means of cotton mealybug incidence for the different localities with 95% confidence limits. Location n Incidence (%) s.e.
2003), to calculate slope, lethal concentration (LC) at 50 and 95% of mortality, confidence limits at 95%, and parallelism (equal slopes) were interpreted using the Chi-square test at a 5% significance level.
Due to the fact that a vast number of terms of the series in ACF graph exceeded confidence limits, a trend is existent in the series.
In addition, the design team quantitatively estimates a range of discharges (confidence limits) based on historical data to evaluate the performance of a plan or project.
In order to determine likely differences between normalized average P-t curves, upper and lower 95% confidence limits were calculated for each average curve and then plotted to form upper and lower control limits.
Dose-response modeling was performed using the Hill model fit to the data by maximum likelihood, with a parametric bootstrap approach for obtaining confidence limits on the PODs derived from the fitted model.
The latent risk time series model yielded forecasts for the number of fatalities per 1, 000 motor vehicles (the fatality risks) that are given in Table 2, including their 68% confidence limits.
Hawaii had a significantly increased risk of death compared to California (hazard ratio: 1.177; 95% confidence limits (1.066-1.300)); Connecticut (hazard ratio: 1.261; 95% confidence limits (1.143-1.390)); Georgia (hazard ratio: 1.257; 95% confidence limits (1.134-1.394)); Iowa (hazard ratio: 1.232; 95% confidence limits (1.119-1.356)); New Mexico (hazard ratio: 1.272; 95% confidence limits (1.151-1.406)).

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