gov.sandia.cognition.statistics.method
Class AnalysisOfVarianceOneWay
java.lang.Object
gov.sandia.cognition.util.AbstractCloneableSerializable
gov.sandia.cognition.statistics.method.AnalysisOfVarianceOneWay
- All Implemented Interfaces:
- BlockExperimentComparison<Number>, NullHypothesisEvaluator<Collection<? extends Number>>, CloneableSerializable, Serializable, Cloneable
@ConfidenceTestAssumptions(name="One-Way Analysis of Variance",
alsoKnownAs={"1-way ANOVA","Fixed-effects 1-way ANOVA","F test"},
description={"ANOVA tests to determine if the means between the various treatments are equal.","ANOVA is a generalization of the paired Student t-test, where there can be multiple treatments.","When there are two groups, a control group and a treatment group, ANOVA is equivalent to the unpaired t-test."},
assumptions={"The data are sampled from a Gaussian distribution.","The variance within the different groups is equal.","The data from each group is collected independently of each other."},
nullHypothesis="The means from all groups are equal.",
dataPaired=false,
dataSameSize=false,
distribution=SnedecorFDistribution.CDF.class,
reference=@PublicationReference(author="Wikipedia",title="Analysis of Variance",type=WebPage,year=2009,url="http://en.wikipedia.org/wiki/Analysis_of_variance"))
public class AnalysisOfVarianceOneWay
- extends AbstractCloneableSerializable
- implements BlockExperimentComparison<Number>
Analysis of Variance single-factor null-hypothesis testing procedure,
usually called "1-way ANOVA".
ANOVA evaluates the probability of the null hypothesis for a Collection of
treatment cases. Each "treatment" is an experiment with a Collection of
results from a given population. You can have different population sizes
in each treatment. The null hypothesis is that there are no differences
between the populations and that observed differences are due to chance.
- Since:
- 2.0
- Author:
- Kevin R. Dixon
- See Also:
- Serialized Form
INSTANCE
public static final AnalysisOfVarianceOneWay INSTANCE
- Default instance.
AnalysisOfVarianceOneWay
public AnalysisOfVarianceOneWay()
- Creates a new instance of AnalysisOfVarianceOneWay
evaluateNullHypothesis
@PublicationReference(author={"Frederick J. Gravetter","Larry B. Wallnau"},
title="Statistics for the Behavioral Sciences",
type=Book,
year=2003,
pages={406,412},
notes="Chapter 13.3")
public AnalysisOfVarianceOneWay.Statistic evaluateNullHypothesis(Collection<? extends Collection<? extends Number>> data)
- Description copied from interface:
BlockExperimentComparison
- Evaluates the null hypothesis for the given block-design treatments
- Specified by:
evaluateNullHypothesis
in interface BlockExperimentComparison<Number>
- Parameters:
data
- Collection of treatments for the block-design experiment, where each
treatment contains
- Returns:
- The confidence for the null hypothesis.
evaluateNullHypothesis
public AnalysisOfVarianceOneWay.Statistic evaluateNullHypothesis(Collection<? extends Number> data1,
Collection<? extends Number> data2)
- Evaluates the ANOVA statistics for the two given treatments, each
treatment can have a different number of samples
- Specified by:
evaluateNullHypothesis
in interface NullHypothesisEvaluator<Collection<? extends Number>>
- Parameters:
data1
- First treatmentdata2
- Second treatment
- Returns:
- ANOVA Confidence statistics