This is a comprehensive data analysis project that focuses on the foundational steps of the data science workflow. The project begins with data cleaning, which involves handling missing values, correcting inconsistencies, and formatting data for analysis. Following this, Exploratory Data Analysis (EDA) is performed to discover patterns, detect outliers, and summarize key characteristics of the dataset, often through visualizations and summary statistics. Finally, the project applies statistical methods to test hypotheses, understand relationships between variables, and draw meaningful conclusions from the data. This project showcases proficiency in data preparation and analytical reasoning, which are crucial skills for any data professional.