Results of 100 simulations (samples include N = 2,000 random observations from Beta distribution) of 0.99 confidence intervals for the population proportion (using the exact method) provide effective coverage of 95%.

<p>Five of the 100 simulations miss the real population proportion <i>p</i> = 0.47, which represents the shaded area below the Beta density function. This proportion indicates a healthy US unemployment rate between .</p

Biomedical example of interval-based parameter estimation - probabilistic representation of the 3D shape of the right hippocampus in the computational Alzheimer's disease brain atlas.

<p>Biomedical example of interval-based parameter estimation - probabilistic representation of the 3D shape of the right hippocampus in the computational Alzheimer's disease brain atlas.</p

Results of a single run of the CI experiment.

<p>Results of a single run of the CI experiment.</p

Confidence intervals using asymptotic properties of maximum likelihood estimates - Poisson distribution with parameter .

<p>Confidence intervals using asymptotic properties of maximum likelihood estimates - Poisson distribution with parameter .</p

Input window of the SOCR confidence interval applet.

<p>Input window of the SOCR confidence interval applet.</p

US Unemployment distribution (1959–2009).

<p>US Unemployment distribution (1959–2009).</p

Confidence interval for proportion : Good coverage using the Clopper-Pearson confidence interval.

<p>Confidence interval for proportion : Good coverage using the Clopper-Pearson confidence interval.</p

Confidence intervals for - sampling from non-normal distribution, .

<p>Confidence intervals for - sampling from non-normal distribution, .</p

Results of 10 runs of the experiment.

<p>Results of 10 runs of the experiment.</p

Input of the experiment when is not known.

<p>Input of the experiment when is not known.</p