Objectives: For this project, you will be working to understand the results of an A/B test run by an e-commerce website. We goal is to 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.
Tools: Used Python, statistical analysis libraries, and data visualization tools for comprehensive A/B testing (numpy, pandas, random, matplotlib, and statsmodels).
Strategies and Techniques: Applied hypothesis testing, statistical significance analysis, confidence interval calculations, and Logistic Regression Modal.
Results 1- that there is no sufficient evidence for reject the null hypothesis ( 𝐻0 ) , and that we do not have sufficient evidence that the new_page has a higher conversion rate than the old_page. 2- the country and the page do not influence on the conversion rate.
Conclusions: And from the above from analysis results would bias me toward suggesting to drop the new page.