Statistical intervals | Statistical forecasting | Regression analysis

Prediction interval

In statistical inference, specifically predictive inference, a prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis. Prediction intervals are used in both frequentist statistics and Bayesian statistics: a prediction interval bears the same relationship to a future observation that a frequentist confidence interval or Bayesian credible interval bears to an unobservable population parameter: prediction intervals predict the distribution of individual future points, whereas confidence intervals and credible intervals of parameters predict the distribution of estimates of the true population mean or other quantity of interest that cannot be observed. (Wikipedia).

Prediction interval
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Quantile | Regression analysis | Mean | Percentile | Chi-squared distribution | Standard score | Credible interval | Standard error | Confidence interval | Bayesian statistics | Confidence and prediction bands | Student's t-distribution | Pivotal quantity | Statistical inference | Journal of Business & Economic Statistics | Parametric statistics | Variance | Posterior probability | Simple linear regression | Extreme value theory | Normal distribution | Extrapolation | Bruno de Finetti | Degrees of freedom (statistics) | Expected value | Sampling (statistics) | Sampling distribution | Ancillary statistic | Sample variance | Statistical model validation