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Skewness

Statistical measure quantifying the asymmetry of a distribution around its mean, where skewness > 0 indicates right skewness and skewness < 0 indicates left skewness.

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Variance stabilization

Process of transforming data to make the variance homogeneous across different levels of the variable, an essential condition for the application of many statistical and ML models.

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Power transformation

Family of transformations of the form x^λ where λ is an optimized parameter, including root transformations (λ=0.5), square transformations (λ=2) and log as a limiting case (λ→0).

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Gaussian distribution

Normal distribution characterized by its symmetric bell curve, a frequent objective of transformations to satisfy the assumptions of many statistical algorithms.

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Lambda parameter

Optimization parameter in Box-Cox and Yeo-Johnson transformations determined by maximum likelihood, controlling the intensity and shape of the applied transformation.

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Inverse hyperbolic transformation

Application of the asinh(x) or artanh(x) function to handle distributions with extremes or bounds, offering a robust alternative to logarithmic transformations.

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Q-Q Plot

Quantile-quantile plot comparing the empirical distribution of data to a theoretical distribution (often normal), an essential visual tool for evaluating the effectiveness of transformations.

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Normality test

Statistical tests (Shapiro-Wilk, Anderson-Darling, Kolmogorov-Smirnov) formally assessing whether data follow a normal distribution after transformation.

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Johnson Transformation

System of flexible transformations based on three families (SB, SU, SL) that can approximate any continuous distribution, offering more flexibility than Box-Cox for complex distributions.

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Kurtosis

Measure of the flatness or peakedness of a distribution compared to the normal distribution, influencing the choice of appropriate transformation to normalize data.

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Quantile Transformation

Non-parametric method transforming data into a specific distribution (normal, uniform) by mapping empirical quantiles to target quantiles.

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Log-normal Distribution

Distribution whose logarithm follows a normal law, common in multiplicative phenomena and an ideal candidate for logarithmic transformation.

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Arcsine Transformation

Application of arcsin(√x) to proportions and percentages bounded between 0 and 1, stabilizing variance for binomial or frequency data.

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Maximum Likelihood

Optimization method used to determine the optimal λ parameter in Box-Cox and Yeo-Johnson transformations by maximizing the likelihood function.

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