normality - Tests for Departure from Normality
A toolkit for assessing data normality using a comprehensive collection of statistical methods. It includes descriptive measures and formal hypothesis tests, such as skewness and kurtosis tests, the Anderson–Darling test, the Shapiro–Wilk test, and the D'Agostino–Pearson K2 omnibus test.
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normal-distributionnormalitystatistics
5.26 score 1 dependents 4 scripts 261 downloadsvarequal - Tests and Measures for Homoscedasticity
Provides statistical methods for assessing homoscedasticity (equality of variances) across groups. The package implements classical and robust tests for variance homogeneity, together with supporting measures and utilities for exploratory analysis and hypothesis testing. These tools can be used as diagnostic procedures prior to analyses that assume equal variances.
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heteroscedasticityhomogeneitystatisticsvariancevariation
5.13 score 1 dependents 248 downloadsoneway - One-Way Statistical Analyses
Performs one-way tests of assumptions (normality and homoscedasticity), analysis of variance, robust and nonparametric alternatives, multiple comparison procedures, effect size estimators, confidence intervals, and descriptive summaries. Functions are designed with a consistent interface to support reproducible and user-friendly statistical workflows. For more details see Howell (2010, ISBN:978-0-495-59784-1), Zar (2014, ISBN:978-0-13-100846-5), Hollander et al. (2014, ISBN:978-0-470-38737-5), Montgomery (2017, ISBN:978-1-119-11347-8), Lakens (2013) <doi:10.3389/fpsyg.2013.00863>, and Piepho (2004) <doi:10.1198/1061860043515>.
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multiple-comparison-procedurespairwise-comparisonpost-hocstatistics
4.78 score 2 scripts 460 downloadsvenny - Venn Diagram
Generate Venn plots, summary tables, and ellipse paths for polygon clipping. Provides direct access to subsets of interest and offers flexible customization of Venn diagrams. Summary tables are also available when Venn diagram visualization is not suitable.
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data-visualizationggplotset-operationsvenn
4.65 score 414 downloadsoutlying - Outliers Detection
Provides functions for detecting outliers in datasets using statistical methods. The package supports identification of anomalous observations in numerical data and is intended for use in data cleaning, exploratory data analysis, and preprocessing workflows.
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data-preprocessingoutliers-detectionstatistics
4.20 score 1 dependents 15 scripts 241 downloads