Analyzing Market Dynamics: An in-Depth Statistical Study of Real Estate Valuations in Tashkent City's Residential Sector Using Advanced Data Analytics Techniques

In this respect, this study zeroes in on real estate trends for City of Tashkent and seeks to use the robust database of all property listings collected in Uybor.uz for the period from January 2015 to September 2023. The study has focused on residential real estate within the metropolitan space. Missing values were judiciously handled by carrying out mean imputation of the data, while outliers were done by means of the IQR method and standardization of numerical variables. We performed the same procedure for the dataset of each country. The statistical summaries have played a major role and have been supported by visualizations for breaking the distributions and links between intervariables. The focus is laid on the Pearson correlation coefficient with respect to linear comments. In addition to the above, we used the Elliptic Envelope Outlier Detection technique and were supported by Mahalonobis Distance for the identification of outliers. Altogether we got 186 outliers, which were 2.51 % of the data. All these measures increase the robustness of the correlation check. Results from post-robustness check revealed there are meaningful linear relationships of size and price, which reflect market behavior. Thus, our methodology and analysis form a deep insight into the housing markets, offering data-driven guidance to all stakeholders. The estimation underlines the role of inliers and outliers in the market analysis and the valuation models call for moderate representation of interpretation to align the implications, which allows the understanding of actual market dynamics and a robust framework for the evaluation of real estate.

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