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Distributional Drift Analysis of Students by pygks458 is a document available to read on EtoBox.

The document presents a distributional drift analysis comparing old and new datasets of 9th-grade student data across three metrics: Attendance, Study Hours, and Total Marks. The analysis utilizes empirical cumulative distribution functions (ECDF) and histograms with kernel density estimates (KDE), revealing significant differences indicated by p-values and Wasserstein distances. Key findings include notable shifts in distributions, with the highest KS statistic observed for Study Hours.

Author
pygks458
Language
EN