There are 0 repository under experiment-design topic.
Ambrosia is a Python library for A/B tests design, split and result measurement
Workshop on basic machine learning, computational modeling, psychophysics, basic data analysis and experiment design
ABacus: fast hypothesis testing and experiment design solution
Optimal Bayesian Experiment Design
A list of resources for research scientists in psychology who use VR/AR/XR
Raspberry Pi Pico firmware for universal hardware control & measurement, along with a user-friendly Python frontend
A Javascript library to conveniently add distribution builders to your online and offline experiments.
Run delayed and risky choice (DARC) experiments using Bayesian Adaptive Design
Design experiments distributed in several batches
A walk through A/B Tests for new feature
Simulation tool for optimal design of high-dimensional MS-based proteomics experiment
An application to easily set up and run online listening experiments for music research.
Jupyter Notebooks for visualizing and exploring empirical model building. http://charlesreid1.github.io/empirical-model-building
El diseño de experimentos es uno de los pilares de la estadística y la ciencia de datos. En este tutorial te explic, que son, como se hacen y los conceptos clave como intervalos de confianzo, p-values, z-scores y más.
Simple and extensible framework for data analysis and machine learning experiments in Python.
This is your the only entry point to deeply understand controlled experiments and begin to use them in practice.
This Streamlit application simulates A/B tests, providing a platform to evaluate the performance of different statistical tests based on data distribution.
Building a simple text priming experiment using jsPsych
Lightweight python experiment tracker.
Experiment design and data analysis package
figsci package performs many functions in efficient scientific graphics, such as phylogenetic barplot, integrated barplot and scatterplot with statistic, and Gantt Chart.
A/B test user splitter PoC, mainly for research and toy projects
Uplift modeling and estimation via the "Uplift Support Vector Machine".
Projects completed for the Data Scientist Nanodegree with Udacity.
The goal of this project is to test new landing page whether it can brings significantly higher conversion rate or not.
Flexible ball-drag-and-drop apps for oTree for dictator games or rule-following tasks.
Experiment design project from Columbia University MSAA 5300 course