Course materials, datasets, and notebooks for Applied Business Statistics (BUSN 5760) at Webster University.
P1: Artificial Intelligence and Machine Learning (AIML) Projects
A reproducible R pipeline for business data integration, quality checks, and economic indicator computation using synthetic firm-level datasets.
This portfolio showcases a collection of data science projects completed during my postgraduate program. The purpose is to demonstrate my acquired skills and abilities in tackling diverse data science challenges. Each project highlights specific techniques and approaches relevant to various aspects of the field.
Python-based business statistics analysis covering probability distributions, hypothesis testing, and decision metrics.
Business Statistics and A/B Testing Analysis
Business Statistics: Used statistical analysis, A/B testing, and data visualization to evaluate whether the new landing page for E-news Express improves subscriber conversion. Analyzed key metrics like time spent and conversion status, and also explored the impact of users’ preferred language on conversion to draw meaningful concl
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