Mathematica
MATHEMATICA COMPATIBILITY INFORMATION

Upgrading from:

Statistics`DescriptiveStatistics`

Functionality in this package has been added to the built-in Mathematica kernel.
is replaced by the kernel function Commonest.

CentralMoment, GeometricMean, HarmonicMean, InterquartileRange, Kurtosis, MeanDeviation, MedianDeviation, QuartileDeviation, Quartiles, QuartileSkewness, RootMeanSquare, Skewness, and TrimmedMean are now part of the built-in Mathematica kernel:

Version 5.2 << Statistics`DescriptiveStatistics`; GeometricMean[{10, 50, 10, 15, 20}]
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is replaced by Commonest:

Version 5.2 << Statistics`DescriptiveStatistics`; Mode[{10, 50, 10, 15, 20}]
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can be computed using Mean and StandardDeviation:

Version 5.2 << Statistics`DescriptiveStatistics`; CoefficientOfVariation[{10, 50, 10, 15, 20}]
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can be computed using Mean:

Version 5.2 << Statistics`DescriptiveStatistics`; ExpectedValue[Sqrt, Range[1., 10.]]
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can be computed using Min and Max:

Version 5.2 << Statistics`DescriptiveStatistics`; SampleRange[{10, 50, 10, 15, 20}]
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can be computed from Kurtosis:

Version 5.2 << Statistics`DescriptiveStatistics`; KurtosisExcess[{10, 50, 10, 15, 20}]
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can be computed by subtracting the mean from the data:

Version 5.2 << Statistics`DescriptiveStatistics`; ZeroMean[{10, 50, 10, 15, 20}]
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can be computed from Mean and StandardDeviation:

Version 5.2 << Statistics`DescriptiveStatistics`; Standardize[Range[1., 10.], MLE -> True]
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can be computed as a parameterized Quantile:

Version 5.2 << Statistics`DescriptiveStatistics`; InterpolatedQuantile[{10, 50, 10, 15, 20}, 3/4]
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, , and can be constructed directly from the report elements:

Version 5.2 << Statistics`DescriptiveStatistics`; LocationReport[{10, 50, 10, 15, 20}]
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Alternate standard deviations and variances can be computed from StandardDeviation and Variance:

Version 5.2 << Statistics`DescriptiveStatistics`; StandardDeviationMLE[{10, 50, 10, 15, 20}]
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Version 5.2 << Statistics`DescriptiveStatistics`; VarianceMLE[{10, 50, 10, 15, 20}]
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Version 5.2 << Statistics`DescriptiveStatistics`; StandardErrorOfSampleMean[{10, 50, 10, 15, 20}]
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Version 5.2 << Statistics`DescriptiveStatistics`; VarianceOfSampleMean[{10, 50, 10, 15, 20}]
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Pearson skewness measures can be computed from basic statistics:

Version 5.2 << Statistics`DescriptiveStatistics`; PearsonSkewness1[{10, 50, 10, 15, 20}]
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Version 5.2 << Statistics`DescriptiveStatistics`; PearsonSkewness2[{10, 50, 10, 15, 20}]
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