Enum NormalConfidenceInterval

java.lang.Object

java.lang.Enum<NormalConfidenceInterval>

org.apache.commons.statistics.interval.NormalConfidenceInterval

All Implemented Interfaces:

Serializable, Comparable<NormalConfidenceInterval>

public enum NormalConfidenceInterval
extends Enum<NormalConfidenceInterval>

Generate confidence intervals for a normally distributed population.

Since:

1.2

See Also:

• Normal distribution confidence interval (Wikipedia)

Enum Constant Summary

Enum Constants

Enum Constant	Description
MEAN	Create a confidence interval for the true mean of an unknown normally distributed population.
VARIANCE	Create a confidence interval for the true variance of an unknown normally distributed population.

Constructor Summary

Constructors

Modifier	Constructor	Description
private	NormalConfidenceInterval()

Method Summary

Modifier and Type	Method	Description
(package private) abstract Interval	create(double mean, double variance, long n, double alpha)	Create a confidence interval from an independent sample from an unknown normally distributed population with the given error rate.
Interval	fromErrorRate(double mean, double variance, long n, double alpha)	Create a confidence interval from an independent sample from an unknown normally distributed population with the given error rate.
static NormalConfidenceInterval	valueOf(String name)	Returns the enum constant of this type with the specified name.
static NormalConfidenceInterval[]	values()	Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class Enum

clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, toString, valueOf

Methods inherited from class Object

getClass, notify, notifyAll, wait, wait, wait

Enum Constant Details

MEAN

public static final NormalConfidenceInterval MEAN

Create a confidence interval for the true mean of an unknown normally distributed population.

VARIANCE

public static final NormalConfidenceInterval VARIANCE

Create a confidence interval for the true variance of an unknown normally distributed population.

Constructor Details

NormalConfidenceInterval

private NormalConfidenceInterval()

Method Details

values

public static NormalConfidenceInterval[] values()

Returns an array containing the constants of this enum type, in the order they are declared.

Returns:

an array containing the constants of this enum type, in the order they are declared

valueOf

public static NormalConfidenceInterval valueOf(String name)

Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)

Parameters:

name - the name of the enum constant to be returned.

Returns:

the enum constant with the specified name

Throws:

IllegalArgumentException - if this enum type has no constant with the specified name

NullPointerException - if the argument is null

fromErrorRate

public Interval fromErrorRate(double mean,
 double variance,
 long n,
 double alpha)

Create a confidence interval from an independent sample from an unknown normally distributed population with the given error rate.

The error rate alpha is related to the confidence level that the interval contains the true probability of success as alpha = 1 - confidence, where confidence is the confidence level in [0, 1]. For example a 95% confidence level is an alpha of 0.05.

The unbiased variance is the sum of the squared deviations from the mean divided by n - 1.

Parameters:

mean - Sample mean.

variance - Unbiased sample variance.

n - Sample size.

alpha - Desired error rate that the true probability of success falls outside the returned interval.

Returns:

Confidence interval containing the target with error rate alpha

Throws:

IllegalArgumentException - if n <= 1, or if alpha is not in the open interval (0, 1).

create

abstract Interval create(double mean,
 double variance,
 long n,
 double alpha)

Create a confidence interval from an independent sample from an unknown normally distributed population with the given error rate.

Parameters:

mean - Sample mean.

variance - Unbiased sample variance.

n - Sample size.

alpha - Desired error rate.

Returns:

Confidence interval