E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing
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A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these. For this project, you will be working to understand the results of an A/B test run by an e-commerce website. Your goal is to work through this notebook to help the company understand if th…
Jupyter Notebook Praktikum Projects. This is repository with data analyst educational projects from Yandex.Praktikum.
This repository contains my academic marketing and customer data analytics related projects using R and SQL.
Udacity Data Analyst Nanodegree - Project III
Analysis of mock A/B Test Results by an e-commerce company. Application of probability, hypothesis testing, sampling distribution, two-sample z-test, and logistic regression to determining whether the company should implement the new web page it developed to increase users' conversion rate
Analysis of the results of an A/B test for an e-commerce website.
Basic Hugo site for AB testing
A/B Testing for E-commerce website
A/B testing with Google Tag Manager: the free and lean solution. A simple web-based tool to instantly generate a ready-to-import Google Tag Manager container (.json) for a classic A/B test.
In this project, I am performing A/B testing for the company’s new website. I performed hypothesis testing with Python and NumPy to determine p-value and used regression models to advise if the company should launch a new website. The result is robust statistical analysis and interpretation of results to ensure the right decision for the company.
Code behind aurimas.eu blog posts
Covariate Adjustment in Randomized Trials
Udacity's DAND 6th project,using the given data about a new website page being launched. Using the techniques of bootstrapping, A/B Test and logistic regression model.
An analysis of A/B Test results to help an e-commerce site decide whether or not they should implement a new page design.
A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.
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