Class IntervalUtils
- java.lang.Object
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- org.apache.commons.math4.legacy.stat.interval.IntervalUtils
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public final class IntervalUtils extends Object
Factory methods to generate confidence intervals for a binomial proportion. The supported methods are:- Agresti-Coull interval
- Clopper-Pearson method (exact method)
- Normal approximation (based on central limit theorem)
- Wilson score interval
- Since:
- 3.3
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static ConfidenceIntervalgetAgrestiCoullInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)Create an Agresti-Coull binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.static ConfidenceIntervalgetClopperPearsonInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)Create a Clopper-Pearson binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.static ConfidenceIntervalgetNormalApproximationInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)Create a binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level using the Normal approximation to the binomial distribution.static ConfidenceIntervalgetWilsonScoreInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)Create a Wilson score binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.
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Method Detail
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getAgrestiCoullInterval
public static ConfidenceInterval getAgrestiCoullInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)
Create an Agresti-Coull binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.- Parameters:
numberOfTrials- number of trialsnumberOfSuccesses- number of successesconfidenceLevel- desired probability that the true probability of success falls within the returned interval- Returns:
- Confidence interval containing the probability of success with
probability
confidenceLevel - Throws:
NotStrictlyPositiveException- ifnumberOfTrials <= 0.NotPositiveException- ifnumberOfSuccesses < 0.NumberIsTooLargeException- ifnumberOfSuccesses > numberOfTrials.OutOfRangeException- ifconfidenceLevelis not in the interval(0, 1).
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getClopperPearsonInterval
public static ConfidenceInterval getClopperPearsonInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)
Create a Clopper-Pearson binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.Preconditions:
numberOfTrialsmust be positivenumberOfSuccessesmay not exceednumberOfTrialsconfidenceLevelmust be strictly between 0 and 1 (exclusive)
- Parameters:
numberOfTrials- number of trialsnumberOfSuccesses- number of successesconfidenceLevel- desired probability that the true probability of success falls within the returned interval- Returns:
- Confidence interval containing the probability of success with
probability
confidenceLevel - Throws:
NotStrictlyPositiveException- ifnumberOfTrials <= 0.NotPositiveException- ifnumberOfSuccesses < 0.NumberIsTooLargeException- ifnumberOfSuccesses > numberOfTrials.OutOfRangeException- ifconfidenceLevelis not in the interval(0, 1).
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getNormalApproximationInterval
public static ConfidenceInterval getNormalApproximationInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)
Create a binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level using the Normal approximation to the binomial distribution.- Parameters:
numberOfTrials- number of trialsnumberOfSuccesses- number of successesconfidenceLevel- desired probability that the true probability of success falls within the interval- Returns:
- Confidence interval containing the probability of success with
probability
confidenceLevel
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getWilsonScoreInterval
public static ConfidenceInterval getWilsonScoreInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)
Create a Wilson score binomial confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.- Parameters:
numberOfTrials- number of trialsnumberOfSuccesses- number of successesconfidenceLevel- desired probability that the true probability of success falls within the returned interval- Returns:
- Confidence interval containing the probability of success with
probability
confidenceLevel - Throws:
NotStrictlyPositiveException- ifnumberOfTrials <= 0.NotPositiveException- ifnumberOfSuccesses < 0.NumberIsTooLargeException- ifnumberOfSuccesses > numberOfTrials.OutOfRangeException- ifconfidenceLevelis not in the interval(0, 1).
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