Libraries.Compute.Statistics.Reporting.CompareVariancesResult Documentation
This class represents data that comes back from a CompareVariances calculation.
Inherits from: Libraries.Compute.Statistics.Reporting.CompareMeansResult, Libraries.Language.Object, Libraries.Compute.Statistics.Reporting.StatisticalTestResult
Actions Documentation
Compare(Libraries.Language.Object object)
This action compares two object hash codes and returns an integer. The result is larger if this hash code is larger than the object passed as a parameter, smaller, or equal. In this case, -1 means smaller, 0 means equal, and 1 means larger. This action was changed in Quorum 7 to return an integer, instead of a CompareResult object, because the previous implementation was causing efficiency issues.
Parameters
- Libraries.Language.Object: The object to compare to.
Return
integer: The Compare result, Smaller, Equal, or Larger.
Example
Object o
Object t
integer result = o:Compare(t) //1 (larger), 0 (equal), or -1 (smaller)
EqualVariances(boolean equalVariances)
Stores the degrees of freedom for each group or test statistic, some may have multiple dfs calculated Examples: SetInformation("A", "between", 4) SetInformation("A", "within", 2)
Parameters
- boolean equalVariances
Equals(Libraries.Language.Object object)
This action determines if two objects are equal based on their hash code values.
Parameters
- Libraries.Language.Object: The to be compared.
Return
boolean: True if the hash codes are equal and false if they are not equal.
Example
use Libraries.Language.Object
use Libraries.Language.Types.Text
Object o
Text t
boolean result = o:Equals(t)
GetAssumptionTestSummary()
Returns the summaries of any assumption tests (if conducted)
Return
text:
GetChartResult()
GetColumnList()
For use in N-sample parametric tests
Return
text:
GetColumns()
GetCorrection()
Return
number
GetCorrectionName()
Return
text
GetCriticalValue()
This indicates the critical value for any statistical test that was run
Return
number: the critical value
GetDegreesOfFreedom()
The degrees of freedom (if only one) calculated for this result.
Return
number:
GetDegreesOfFreedomTable()
GetDegreesOfFreedomTable(text source)
The hash table of df-values for this source, could have one or more
Parameters
- text source
Return
GetDistributionResults()
GetDistributionTest()
Saved test for normality test (if conducted)
Return
GetEasySummary()
This action summarizes the result and lists it informally.
Return
text:
GetEffectSize()
The effect size (if only one) calculated for this result.
Return
number:
GetEffectSizeName()
The effect size name (if only one) calculated for this result.
Return
text:
GetEffectSizesTable(text source)
The hash table of effect sizes for this source, could have one or more
Parameters
- text source
Return
GetEffectSizesTable()
GetExperimentalDesign()
GetFactorList()
List of factors/effects from test
Return
text:
GetFactors()
GetFormalNumericalResult()
This action summarizes the result and places it into formal academic language, in APA format. For more information: https://apastyle.apa.org/instructional-aids/numbers-statistics-guide.pdf
Return
text:
GetFormalSummary()
This action summarizes the result and places it into formal academic language, in APA format. For more information: https://apastyle.apa.org/instructional-aids/numbers-statistics-guide.pdf
Return
text:
GetFormalTestName()
Returns the name of the test in formal mathematical language.
Return
text: the name of the test in mathematical language.
GetFormat()
Returns true if this result is significant against the significance level
Return
Libraries.Compute.Statistics.Reporting.StatisticsFormatting:
GetGreenhouseGeisserCorrection()
Return
number
GetGroupsFrame()
The effect size (if only one) calculated for this result.
Return
GetGroupsTable()
GetHashCode()
This action gets the hash code for an object.
Return
integer: The integer hash code of the object.
Example
Object o
integer hash = o:GetHashCode()
GetHuynhFeldtCorrection()
Return
number
GetInformation()
GetLowerBoundCorrection()
Return
number
GetMatrixInformation()
The hash table of effect sizes for this source, could have one or more
Return
GetPairwiseResults()
GetPairwiseSummary()
Returns the summary of a CompareMeansPairwise test in CompareMeans (if conducted)
Return
text:
GetPairwiseTest()
Saved test for pairwise post hoc test (if conducted)
Return
GetProbabilityValue()
The p-value (if only one) calculated for this result.
Return
number:
GetProbabilityValuesTable()
GetProbabilityValuesTable(text source)
The hash table of p-values for this source, could have one or more
Parameters
- text source
Return
GetReportResult(Libraries.System.File file)
This action summarizes the result and creates a HTML file with the contents.
Parameters
GetSignificanceLevel()
Obtains the significance level.
Return
number: the significance level.
GetSources()
GetSummary()
This action summarizes the result and lists it informally.
Return
text:
GetSummaryDataFrame()
This action summarizes the result and puts it in a frame.
Return
GetTestStatistic()
The test statistic (if only one) calculated for this result.
Return
number:
GetTestStatisticName()
The test statistic name (if only one) calculated for this result.
Return
text:
GetTestStatisticsTable(text source)
The hash table of test statistics for this source, could have one or more
Parameters
- text source
Return
GetTestStatisticsTable()
GetVarianceResult()
Saved result for equal variance test (if conducted)
Return
Libraries.Compute.Statistics.Reporting.CompareVariancesResult:
GetVarianceTest()
Saved test for variance equality test (if conducted)
Return
HasEqualVariances()
The degrees of freedom (if only one) calculated for this result.
Return
boolean:
HasNormalDistribution()
The full double hash table of p-values
Return
boolean:
IsRanked()
The test statistic name (if only one) calculated for this result.
Return
boolean:
IsRepeated()
The hash table of test statistics for this source, could have one or more
Return
boolean:
IsSignificant()
Return
boolean
NormalDistribution(boolean normalDistribution)
The hash table of p-values for this source, could have one or more
Parameters
- boolean normalDistribution
Ranked(boolean ranked)
Stores the test statistic for each group, some groups may have multiple test statistics calculated Examples: SetInformation("A", "T", 1.34) SetInformation("A", "Wilk's Lambda", 1.39)
Parameters
- boolean ranked
Repeated(boolean repeated)
The test statistic (if only one) calculated for this result.
Parameters
- boolean repeated
Save(text path)
This action is overwritten in descendent classes.
Parameters
- text path
SetColumns(Libraries.Containers.Array<text> columns)
SetCriticalValue(number criticalValue)
This sets the critical value for any statistical test that was run
Parameters
- number criticalValue
SetDegreesOfFreedom(text source, text dfName, number dfValue)
Stores the degrees of freedom for each group or test statistic, some may have multiple dfs calculated Examples: SetInformation("A", "between", 4) SetInformation("A", "within", 2)
Parameters
- text source
- text dfName
- number dfValue
SetDegreesOfFreedom(number degreesOfFreedom)
Sets the degrees of freedom value (df in statistics) calculated by the test.
Parameters
- number degreesOfFreedom: the degrees of freedom
SetDistributionResults(Libraries.Containers.Array<Libraries.Compute.Statistics.Reporting.CompareDistributionsResult> distributionResults)
SetDistributionTest(Libraries.Compute.Statistics.Tests.CompareDistributions test)
Saved test for normality test (if conducted)
Parameters
SetEffectSize(text source, text effectName, number effectSize)
Stores the effect size for each group, some groups may have multiple effect sizes calculated Examples: SetInformation("A", "Cohen's D", 1.2) SetInformation("A", "Eta-Squared", 0.52)
Parameters
- text source
- text effectName
- number effectSize
SetEffectSize(number effectSize)
Sets the effect size used for this test.
Parameters
- number effectSize: is the effect size used for this test.
SetEffectSizeName(text effectSizeName)
Sets the name of the effect size used for this test.
Parameters
- text effectSizeName: is the name of the effect size used for this test.
SetExperimentalDesign(Libraries.Compute.Statistics.Tests.ExperimentalDesign design)
SetFactors(Libraries.Containers.Array<text> factors)
SetFormalTestName(text formalTestName)
Sets the name of the test in formal mathematical language.
Parameters
- text formalTestName: the name of the test in mathematical language.
SetFormat(Libraries.Compute.Statistics.Reporting.StatisticsFormatting format)
Sets the significance level of the test (default is 0.05).
Parameters
SetGroupsFrame(Libraries.Compute.Statistics.DataFrame groupsFrame)
The effect size name (if only one) calculated for this result.
Parameters
SetGroupsTable(Libraries.Containers.HashTable<text:Libraries.Compute.Statistics.DataFrame> groupsTable)
Stores the effect size for each group, some groups may have multiple effect sizes calculated Examples: SetInformation("A", "Cohen's D", 1.2) SetInformation("A", "Eta-Squared", 0.52)
Parameters
SetInformation(text source, text infoName, number infoValue)
Stores the other information for each group, could include summary values, sum of squares etc Examples: SetInformation("A", "Mean", 10) SetInformation("A", "Sum Of Squares", 32.45)
Parameters
- text source
- text infoName
- number infoValue
SetInformation(text source, text infoName, Libraries.Compute.Matrix infoValue)
Stores the other information for each group, could include summary values, sum of squares etc Examples: SetInformation("A", "Mean", 10) SetInformation("A", "Sum Of Squares", 32.45)
Parameters
- text source
- text infoName
- Libraries.Compute.Matrix
SetPairwiseResults(Libraries.Containers.Array<Libraries.Compute.Statistics.Reporting.CompareMeansResult> pairwise)
SetPairwiseTest(Libraries.Compute.Statistics.Tests.CompareMeansPairwise test)
Saved test for pairwise post hoc test (if conducted)
Parameters
SetProbabilityValue(number probabilityValue)
Sets the probability value (p in statistics) calculated by the test.
Parameters
- number probabilityValue: the probability
SetProbabilityValue(text source, text statistic, number probabilityValue)
Stores the p-value for each group and test statistic Example: SetInformation("A", "t", 0.05)
Parameters
- text source
- text statistic
- number probabilityValue
SetSignificanceLevel(number significanceLevel)
Sets the significance level of the test (default is 0.05).
Parameters
- number significanceLevel: the significance level between 0 and 1.
SetSources(Libraries.Containers.Array<text> sources)
SetTestStatistic(number testStatistic)
This sets the calculated test statistic for any statistical test that was run
Parameters
- number testStatistic
SetTestStatistic(text source, text statName, number testStatistic)
Stores the test statistic for each group, some groups may have multiple test statistics calculated Examples: SetInformation("A", "T", 1.34) SetInformation("A", "Wilk's Lambda", 1.39)
Parameters
- text source
- text statName
- number testStatistic
SetVarianceResult(Libraries.Compute.Statistics.Reporting.CompareVariancesResult varianceResult)
Saved result for equal variance test (if conducted)
Parameters
SetVarianceTest(Libraries.Compute.Statistics.Tests.CompareVariances test)
Saved test for variance equality test (if conducted)
Parameters
UseFApproximation(boolean useFApproximation)
Used in multivariate tests
Parameters
- boolean useFApproximation
UseFApproximation()
Used in multivariate tests
Return
boolean:
UseHotellingStatistic(boolean useHotelling)
Used in multivariate tests
Parameters
- boolean useHotelling
UseHotellingStatistic()
Used in multivariate tests
Return
boolean:
UsePillaiStatistic(boolean usePillai)
Used in multivariate tests
Parameters
- boolean usePillai
UsePillaiStatistic()
Used in multivariate tests
Return
boolean:
UseWilksStatistic()
Used in multivariate tests
Return
boolean:
UseWilksStatistic(boolean useWilks)
Used in multivariate tests
Parameters
- boolean useWilks
UseX2Approximation()
Used in multivariate tests
Return
boolean:
UseX2Approximation(boolean useX2Approximation)
Used in multivariate tests
Parameters
- boolean useX2Approximation
On this page
Variables TableAction Documentation- Compare(Libraries.Language.Object object)
- EqualVariances(boolean equalVariances)
- Equals(Libraries.Language.Object object)
- GetAssumptionTestSummary()
- GetChartResult()
- GetColumnList()
- GetColumns()
- GetCorrection()
- GetCorrectionName()
- GetCriticalValue()
- GetDegreesOfFreedom()
- GetDegreesOfFreedomTable()
- GetDegreesOfFreedomTable(text source)
- GetDistributionResults()
- GetDistributionTest()
- GetEasySummary()
- GetEffectSize()
- GetEffectSizeName()
- GetEffectSizesTable(text source)
- GetEffectSizesTable()
- GetExperimentalDesign()
- GetFactorList()
- GetFactors()
- GetFormalNumericalResult()
- GetFormalSummary()
- GetFormalTestName()
- GetFormat()
- GetGreenhouseGeisserCorrection()
- GetGroupsFrame()
- GetGroupsTable()
- GetHashCode()
- GetHuynhFeldtCorrection()
- GetInformation()
- GetLowerBoundCorrection()
- GetMatrixInformation()
- GetPairwiseResults()
- GetPairwiseSummary()
- GetPairwiseTest()
- GetProbabilityValue()
- GetProbabilityValuesTable()
- GetProbabilityValuesTable(text source)
- GetReportResult(Libraries.System.File file)
- GetSignificanceLevel()
- GetSources()
- GetSummary()
- GetSummaryDataFrame()
- GetTestStatistic()
- GetTestStatisticName()
- GetTestStatisticsTable(text source)
- GetTestStatisticsTable()
- GetVarianceResult()
- GetVarianceTest()
- HasEqualVariances()
- HasNormalDistribution()
- IsRanked()
- IsRepeated()
- IsSignificant()
- NormalDistribution(boolean normalDistribution)
- Ranked(boolean ranked)
- Repeated(boolean repeated)
- Save(text path)
- SetColumns(Libraries.Containers.Array
columns) - SetCriticalValue(number criticalValue)
- SetDegreesOfFreedom(text source, text dfName, number dfValue)
- SetDegreesOfFreedom(number degreesOfFreedom)
- SetDistributionResults(Libraries.Containers.Array
distributionResults) - SetDistributionTest(Libraries.Compute.Statistics.Tests.CompareDistributions test)
- SetEffectSize(text source, text effectName, number effectSize)
- SetEffectSize(number effectSize)
- SetEffectSizeName(text effectSizeName)
- SetExperimentalDesign(Libraries.Compute.Statistics.Tests.ExperimentalDesign design)
- SetFactors(Libraries.Containers.Array
factors) - SetFormalTestName(text formalTestName)
- SetFormat(Libraries.Compute.Statistics.Reporting.StatisticsFormatting format)
- SetGroupsFrame(Libraries.Compute.Statistics.DataFrame groupsFrame)
- SetGroupsTable(Libraries.Containers.HashTable
- SetInformation(text source, text infoName, number infoValue)
- SetInformation(text source, text infoName, Libraries.Compute.Matrix infoValue)
- SetPairwiseResults(Libraries.Containers.Array
pairwise) - SetPairwiseTest(Libraries.Compute.Statistics.Tests.CompareMeansPairwise test)
- SetProbabilityValue(number probabilityValue)
- SetProbabilityValue(text source, text statistic, number probabilityValue)
- SetSignificanceLevel(number significanceLevel)
- SetSources(Libraries.Containers.Array
sources) - SetTestStatistic(number testStatistic)
- SetTestStatistic(text source, text statName, number testStatistic)
- SetVarianceResult(Libraries.Compute.Statistics.Reporting.CompareVariancesResult varianceResult)
- SetVarianceTest(Libraries.Compute.Statistics.Tests.CompareVariances test)
- UseFApproximation(boolean useFApproximation)
- UseFApproximation()
- UseHotellingStatistic(boolean useHotelling)
- UseHotellingStatistic()
- UsePillaiStatistic(boolean usePillai)
- UsePillaiStatistic()
- UseWilksStatistic()
- UseWilksStatistic(boolean useWilks)
- UseX2Approximation()
- UseX2Approximation(boolean useX2Approximation)