Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

Minimal A/B Testing Library in PHP

This python project is a helper package that uses power analysis to calculate required sample size for any experiment

A web application to design and evaluate the results of A/B tests.

Design of single- and multi-stage multi-arm clinical trials

Free WordPress Plugin: This sample size calculator enables you to calculate the minimum sample size and the margin of error. Learn about sample size, the margin of error, & confidence interval. www.calculator.io/sample-size-calculator/

Survey Planning Tools

Project repository of the Matters Arising commentary "Multivariate BWAS can be replicable with moderate sample sizes in some cases""

MinSizeML (Minimum Size for Machine Learning) R package that contains functions to estimate the minimum sample size for machine learning

Tools for power analysis, sample size requirements, minimum detectable effects (MDE) calculation

Collection of scripts and modules for biostatistics and data science simple automation for research process.

Code for the paper "Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation"

Calculate statistical power for longitudinal linear mixed-effects models with dropout. Supports null hypothesis, non-inferiority, and equivalence tests.

Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Chi-Squared Test

Simulation-based sample size tools for prediction models

jamovi wrapper for pwrss package

Sample size and power for association studies involving mitochondrial DNA haplogroups -

A/B tests calc

The Bias-Variance Tradeoff Visualization project provides an interactive tool to understand the bias-variance tradeoff in machine learning models. It visually demonstrates how different models perform on training and validation datasets, helping users grasp the concepts of overfitting and underfitting.

Independent validation suite for Zetyra statistical calculators. 169 tests across GSD, CUPED, and Bayesian Toolkit — benchmarked against gsDesign, scipy, conjugate priors, and published trials (HPTN 083, HeartMate II, REBYOTA).