A visualization of the relationships among the five elements in experimental power analysis.
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Updated
Jan 10, 2026 - Python
A visualization of the relationships among the five elements in experimental power analysis.
In this Project I Used Hypothesis testing To gain insights and Explore strategies to enhance taxi revenue through an in-depth analysis of payment methods. This repo dives into the correlation between payment types and fare pricing, offering valuable recommendations for optimizing earnings without compromising customer satisfaction.
Objective: Cleaned, analyzed, and detected anomalies in financial data to support decision-making. Utilized Power BI, Tableau, and Excel for dashboard creation and SQL for data extraction. Key insights included 12k room revenue and a 58.80% occupancy rate, driving financial decisions.
Python Learning Series
Attempting to determine value in the NFL Draft
Data analysis comparing the performance of Facebook and AdWords ad campaigns in 2019, Using Statical Methods such as A/B test focusing on clicks, conversions, cost-effectiveness, and seasonal trends.
Python-based implementation of Mean, Median, and Mode for basic statistical analysis.
Conducted data cleaning, exploratory data analysis (EDA), and using SQL for efficient data exploration and pattern identification. Used basic statistical analysis to understand relationships between variables. •Tools/Technologies: Python (Pandas, Matplotlib, Seaborn), SQL ,Jupyter Notebook and SQL Workbench.
Questa repository contiene il codice e i materiali relativi alla tesi magistrale, con un focus su analisi statistiche ed analisi predittive. Include strumenti e metodi per esplorare e modellare i dati, con tecniche statistiche avanzate come la regressione logistica, analisi di clustering, e metodi di ML e DL per la previsione e classificazione
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