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Enhancing `{ggplot2}` plots with statistical analysis 📊 🎨 📣
Statistical package in Python based on Pandas
Updated
Mar 19, 2022
Python
🐉 Compute and work with indices of effect size and standardized parameters
MAVIS: Meta Analysis via Shiny
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).
Updated
Mar 11, 2022
Jupyter Notebook
Collection of Matlab functions for the computation of measures of effect size
Updated
Nov 12, 2018
MATLAB
The Scott-Knott Effect Size Difference (ESD) test
Effect Size Computation for Meta Analysis
An R package for visualizing comparison between two distributions.
Updated
Feb 6, 2022
Julia
Interpret effects and visualise uncertainty
EASI: Estimation Approach to Statistical Inference
Computation and visualization of standardized mean differences from simulated data
Updated
Oct 29, 2020
MATLAB
Identifying and avoiding common misinterpretations in using statistics
Updated
Jul 2, 2018
Jupyter Notebook
Exploring the bias and cis for cohen's d
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.
This script computes two indices of effect size for pairwise comparisons based on the Mann Whitney U statistic.
Magnitude of the Effect - An Effect Size and CI calculator
A Shiny R web application to estimate differences in diagnostic efficiency based on differences between single-condition cases.
Tidy Data Frames of Marginal Effects for ggplot2
Shiny App for comparison of samples and plotting effect size
Shiny App for comparison of samples
Social studies lab dedicated to preferences between NA and EU in board games
Updated
Sep 6, 2021
Jupyter Notebook
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Currently, we load
inst/example.csvfrom disk in every test. This should only be loaded once before all the tests.