Enhancing {ggplot2} plots with statistical analysis 📊📣
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Updated
May 15, 2024 - R
Enhancing {ggplot2} plots with statistical analysis 📊📣
Statistical package in Python based on Pandas
This repository contains analysis of churn in telephone service company (using IV and WOE), comparison of effect size and information value and quick tutorial how to use information value module (created for this analysis).
🐉 Compute and work with indices of effect size and standardized parameters
Collection of Matlab functions for the computation of measures of effect size
The Scott-Knott Effect Size Difference (ESD) test
Effect size measures
A MATLAB package for multivariate permutation testing and effect size measurement
An R package for visualizing comparison between two distributions.
A Python package for computing effect sizes
Interpret effects and visualise uncertainty
This code is an implementation of the A statistic, otherwise known as the probability of superiority, in SAS. The A statistic is a non-parametric form of the common language effect-size. Both it and its counterpart, RProbSup, are available at the website linked below.
Identifying and avoiding common misinterpretations in using statistics
Two sample data analysis method that tests for negligible and meaningful effect sizes (through difference in means)
Effect-Size-Based Meta-Analysis for Multi-Dataset Evaluation of RecSys Experiments
Calculating robust effect sizes using bootstrap (resampling) technique in R.
This script computes two indices of effect size for pairwise comparisons based on the Mann Whitney U statistic.
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