Udacity nanodegree projects: DLND, DRLND, DAND

A/B Testing Result Analysis on Total Conversion

For this project, I will be working to understand the results of an A/B test run by an e-commerce website. The goal is to work through this notebook to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.

This repository showcases an infrastructure designed for analyzing A/B tests in mobile games. It leverages BigQuery to process Firebase and GA4-based event data and uses Looker Studio for dynamic visualization. The project simplifies A/B test comparisons, enabling stakeholders to view results directly through interactive dashboards.

This is a Python reproduction of the original case study performed in R language- 'A/B Testing with Machine Learning - A Step-by-Step Tutorial written by Matt Dancho of Business Science'

Udacity Project 2 - AB Testing Analysis. Utilize practical statistics, regression, and other data analysis tools to help the company determine if they should implement a new webpage.

Using SQL we analyze the AB Test results to determine which test has the best effectiveness based on customer views and order response

MDE calculator for AB testing projects to calculate your sample size properly.

A/B tests for themes case study

A/B testing Project for Cookie Cats Mobile Game

This project is about A/B testing experiment conducted by Udacity, an e-learning platform, with the goal of reducing the number of users who leave the course at the end of the free-trial period.

Frequentist A/B-test RPU Calculator in PyShiny

AB Testing analysis from Udacity, including determining the experiment size and analyzing the results.

This project evaluates revenue outcomes from three promotional campaigns to identify the most effective approach for launching a new product.

statistical infos (z-/p-values) for AB testing

Projects completed for Data Analyst Course by Yandex.Practicum. Main working tools: Python and Pandas.

AB testing fror made up fashion E-Commerce company ChicBeads [Python, Tableau]

Replication of a RCT (A/B Test) originally done by Dr. Andrew Friedson.

An A/B test run by an e-commerce website. my goal is to work through this notebook to help the company understand if they should implement the new page, keep the old page, or perhaps run the experiment longer to make their decision.

The data to be used is a part of the 2018 BRFSS Survey Data prepared by CDC. Data cleaning and EDA was performed before modeling. 6 algorithms was applied to build the classification models. Performance were evaluated across metrics of accuracy, precision, recall, F1, and AUC-ROC scores.