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

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

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:

GetColumnList()

For use in N-sample parametric tests

Return

text:

GetColumns()

List of factor headers from original frame

Return

Libraries.Containers.Array:

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(text source)

The hash table of df-values for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetDegreesOfFreedomTable()

The full double hash table of df-values

Return

Libraries.Containers.HashTable:

GetDistributionResults()

Saved results for normal distribution test (if conducted)

Return

Libraries.Containers.Array:

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()

The full double hash table of effect sizes

Return

Libraries.Containers.HashTable:

GetEffectSizesTable(text source)

The hash table of effect sizes for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetFactorList()

List of factors/effects from test

Return

text:

GetFactors()

List of factors/effects from test

Return

Libraries.Containers.Array:

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

Libraries.Compute.Statistics.DataFrame:

GetGroupsTable()

The full double hash table of stat-values

Return

Libraries.Containers.HashTable:

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()

The full double hash table of effect sizes

Return

Libraries.Containers.HashTable:

GetLowerBoundCorrection()

Return

number

GetMatrixInformation()

The hash table of effect sizes for this source, could have one or more

Return

Libraries.Containers.HashTable:

GetPairwiseResults()

Saved results for pairwise post hoc test (if conducted)

Return

Libraries.Containers.Array:

GetPairwiseSummary()

Returns the summary of a CompareMeansPairwise test in CompareMeans (if conducted)

Return

text:

GetProbabilityValue()

The p-value (if only one) calculated for this result.

Return

number:

GetProbabilityValuesTable()

The full double hash table of p-values

Return

Libraries.Containers.HashTable:

GetProbabilityValuesTable(text source)

The hash table of p-values for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetSignificanceLevel()

Obtains the significance level.

Return

number: the significance level.

GetSources()

For use in N-sample parametric tests

Return

Libraries.Containers.Array:

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

Libraries.Compute.Statistics.DataFrame:

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()

The full double hash table of stat-values

Return

Libraries.Containers.HashTable:

GetTestStatisticsTable(text source)

The hash table of test statistics for this source, could have one or more

Parameters

  • text source

Return

Libraries.Containers.HashTable:

GetVarianceResult()

Saved result for equal variance test (if conducted)

Return

Libraries.Compute.Statistics.Reporting.CompareVariancesResult:

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)

For use in N-sample parametric tests

Parameters

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)

Saved results for normal distribution test (if conducted)

Parameters

SetEffectSize(number effectSize)

Sets the effect size used for this test.

Parameters

  • number effectSize: is the effect size used for this test.

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

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.

SetFactors(Libraries.Containers.Array<text> factors)

List of factors/effects from test

Parameters

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

SetPairwiseResults(Libraries.Containers.Array<Libraries.Compute.Statistics.Reporting.CompareMeansResult> pairwise)

Saved results 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)

For use in 2 and N-sample parametric tests

Parameters

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

UseFApproximation()

Used in multivariate tests

Return

boolean:

UseFApproximation(boolean useFApproximation)

Used in multivariate tests

Parameters

  • boolean useFApproximation

UseHotellingStatistic()

Used in multivariate tests

Return

boolean:

UseHotellingStatistic(boolean useHotelling)

Used in multivariate tests

Parameters

  • boolean useHotelling

UsePillaiStatistic()

Used in multivariate tests

Return

boolean:

UsePillaiStatistic(boolean usePillai)

Used in multivariate tests

Parameters

  • boolean usePillai

UseWilksStatistic()

Used in multivariate tests

Return

boolean:

UseWilksStatistic(boolean useWilks)

Used in multivariate tests

Parameters

  • boolean useWilks

UseX2Approximation(boolean useX2Approximation)

Used in multivariate tests

Parameters

  • boolean useX2Approximation

UseX2Approximation()

Used in multivariate tests

Return

boolean: