(untitled) (DIGITAL TRANSFORMATION AND ARTIFICIAL INTELLIGENCE, 2024)
This investigation delves into Tashkent city’s real estate dynamics by examining a comprehensive dataset of property listings from January 2015 to September 2023, sourced from uybor.uz. Emphasizing residential real estate within the metropolitan expanse, the study rigorously preprocessed the data, ad- dressing missing values with mean imputation, outliers with the Interquartile Range (IQR) method, and standardizing numerical variables. Through Explora- tory Data Analysis (EDA), we leveraged statistical summaries and visualizations to decode distributions and inter-variable correlations, focusing on the Pearson correlation coefficient for linear relationship insights. Utilizing Elliptic Envelope Outlier Detection underpinned by the Mahalanobis distance, we isolated 186 out- liers, constituting 2.51% of the data, to uphold the integrity of our correlation assessment. The refined analysis revealed notable linear correlations between property prices and sizes, indicative of market behavior. Our methodology and analytical outcomes yield profound insights into the housing market’s nuances, equipping stakeholders with data-driven guidance. The discourse on inliers and outliers underscores their influence on market analysis and valuation models, ad- vocating for nuanced interpretations that accommodate market complexity. Our findings illuminate market trends and endorse a fortified framework for real es- tate evaluation, emphasizing the critical role of outliers in understanding the full scope of market dynamics.