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Evaluating Missing Data Imputation Methods for Clustering

baixuezhang
July 10, 2026

About

This project explores whether charitable giving behavior is related to demographic, political, and religious characteristics. Because the survey data contains missing responses, the project also considers how missing data may affect the patterns found through clustering.
The main research questions are whether the dataset contains meaningful cluster structure and whether different imputation methods lead to different clustering results. In other words, the project examines both donor segmentation and the stability of those segments under different missing-data strategies.

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