## Libraries.Compute.Statistics.Tests.CompareVariances Documentation

Example Code

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare = frame:CompareVariances()
output compare:GetFormalSummary()
``````

## Actions Documentation

This action adds a value to the end of the input.

#### Parameters

• integer column

This action adds a value to the end of the input.

#### Parameters

• integer column

### AssumeNormalDistribution(boolean assume)

Used in independent-sample tests

#### Parameters

• boolean assume

### Calculate(Libraries.Compute.Statistics.DataFrame frame)

Used if trimmed mean calculation is necessary

### 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.

#### 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)
``````

### CompareSeveralRelatedVariances(Libraries.Compute.Statistics.DataFrame frame)

Mauchly's Sphericity Test for variance of differences equality (sphericity). Assumptions: 1. Samples are dependent If not dependent: Use Levene's Test > CompareVariances:CompareIndependentVariances Null hypothesis: The variances of the differences are equal across all samples Alternative hypothesis: At least one variance of a difference is not equal to the others.

#### Parameters

Example

``````
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare = frame:CompareRelatedVariances()
output compare:GetFormalSummary()
``````

### CompareSeveralVariances(Libraries.Compute.Statistics.DataFrame frame)

This action tests for variance equality (homogeneity) for 2 or more independent samples. It is commonly used with an ANOVA in CompareMeans. It conducts the following tests: Brown-Forsythe Test > CompareVariances:UseMedianAsCenter() or UseTrimmedMeanAsCenter(0.05) Levene's Test > CompareVariances:UseMeanAsCenter() Assumptions: 1. Samples are independent If not independent: Use Mauchly's Sphericity Test > CompareVariances:CompareSeveralRelatedVariances Null hypothesis: The variances are equal across all samples Alternative hypothesis: At least one variance is not equal to the others.

#### Parameters

Example

``````
use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare = frame:CompareVariances()
output compare:GetFormalSummary()
``````

### EmptyColumns()

This action empty's the list, clearing out all of the items contained within it.

### EmptyFactors()

This action empty's the list, clearing out all of the items contained within it.

### Equals(Libraries.Language.Object object)

This action determines if two objects are equal based on their hash code values.

#### 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)
``````

### GetChart()

#### Return

Libraries.Interface.Controls.Charts.BoxPlot: an array of CompareVariancesResult objects

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

Array<CompareVariancesResult> results = compare:GetResults()
``````

### GetColumn(integer index)

This action gets the item at a given location in an array.

#### Parameters

• integer index

#### Return

integer: The item at the given location.

### GetColumnIterator()

This action gets an iterator for the object and returns that iterator.

#### Return

Libraries.Containers.Iterator: Returns the iterator for an object.

### GetColumnSize()

This action gets the size of the array.

integer:

### GetDegreesOfFreedom()

This returns the degrees of freedom if only one result exists.

#### Return

number: the Degrees of Freedom.

### GetEffectSize()

This returns the effect size if only one result exists.

#### Return

number: the effect size.

### GetExperimentalDesign()

Huynh-Feldt epsilon

### GetFactor(integer index)

This action gets the item at a given location in an array.

#### Parameters

• integer index

#### Return

integer: The item at the given location.

### GetFactorIterator()

This action gets an iterator for the object and returns that iterator.

#### Return

Libraries.Containers.Iterator: Returns the iterator for an object.

### GetFactorSize()

This action gets the size of the array.

integer:

### GetFormalSummary()

This action summarizes the results and places them into formal academic language, in APA format. For more information: https://apastyle.apa.org/instructional-aids/numbers-statistics-guide.pdf

#### Return

text: a condensed formal result of the test

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

output compare:GetFormalSummary()
``````

### GetGroups(Libraries.Compute.Statistics.DataFrame frame)

Gets the the fully factored samples/groups in an array of dataframes. Using an array of dataframes instead of a single dataframe helps with multivariate cases.

### 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()
``````

### GetProbabilityValue()

This returns the probability if only one result exists.

#### Return

number: the P-Value.

### GetReport(Libraries.System.File file)

#### Parameters

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

DataFrame result = compare:GetSummaryDataFrame()
result:Save("myresult.csv")
``````

### GetResult()

This returns a result if only one exists.

#### Return

Libraries.Compute.Statistics.Reporting.CompareVariancesResult: the CompareVariancesResult object

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
compare:Calculate(frame)

CompareVariancesResult result = compare:GetResult()
``````

### GetResults()

#### Return

Libraries.Containers.Array: an array of CompareVariancesResult objects

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

Array<CompareVariancesResult> results = compare:GetResults()
``````

### GetSignificanceLevel()

A list of unique items of the factor

number:

### GetStatisticalFormatting()

Fill in new frame

### GetSummary()

#### Return

text: a list of the important statistics of the test

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

output compare:GetSummary()
``````

### GetSummaryDataFrame()

#### Return

Libraries.Compute.Statistics.DataFrame: a DataFrame of the important statistics of the test

Example

``````use Libraries.Compute.Statistics.DataFrame
use Libraries.Compute.Statistics.Tests.CompareVariances

DataFrame frame

CompareVariances compare
frame:Calculate(compare)

DataFrame result = compare:GetSummaryDataFrame()
result:Save("myresult.csv")
``````

### GetTestStatistic()

This returns the test statistic if only one result exists.

#### Return

number: the test statistic.

### IsEmptyColumns()

This action returns a boolean value, true if the container is empty and false if it contains any items.

#### Return

boolean: Returns true when the container is empty and false when it is not.

### IsEmptyFactors()

This action returns a boolean value, true if the container is empty and false if it contains any items.

#### Return

boolean: Returns true when the container is empty and false when it is not.

### RemoveColumn(integer column)

This action removes the first occurrence of an item that is found in the Addable object.

#### Parameters

• integer column

#### Return

boolean: Returns true if the item was removed and false if it was not removed.

### RemoveColumnAt(integer index)

This action removes an item from an indexed object and returns that item.

#### Parameters

• integer index

### RemoveFactor(integer column)

This action removes the first occurrence of an item that is found in the Addable object.

#### Parameters

• integer column

#### Return

boolean: Returns true if the item was removed and false if it was not removed.

### RemoveFactorAt(integer index)

This action removes an item from an indexed object and returns that item.

#### Parameters

• integer index

### RepeatedMeasures(boolean repeatedMeasures)

Used in dependent-sample tests

#### Parameters

• boolean repeatedMeasures

### SetExperimentalDesign(Libraries.Compute.Statistics.Tests.ExperimentalDesign design)

https://www.originlab.com/doc/en/UserGuide/UserGuide/Algorithms_(Repeated_Measures_ANOVA).html

### SetSignificanceLevel(number significanceLevel)

Sets the significance level of the test (default is 0.05).

#### Parameters

• number significanceLevel: the significance level between 0 and 1.

### SetStatisticalFormatting(Libraries.Compute.Statistics.Reporting.StatisticsFormatting formatting)

Create a new frame based on that list

### UseMeanAsCenter()

Used in independent-sample tests

### UseMedianAsCenter()

Used in independent-sample tests

### UseTrimmedMeanAsCenter(number percent)

Used in independent-sample tests

#### Parameters

• number percent