WITHDRAWN This study explores the integration of real-time analytics with traditional exit polling methods in

Music City Center 

This study explores the integration of real-time analytics with traditional exit polling methods in the context of Ghana's 2024 presidential election, aiming to enhance electoral transparency and accuracy. Employing an innovative three-tier sampling approach, the research combined stratified sampling, cluster sampling, and simple random sampling to ensure representative data and reduce bias. Trained personnel at randomly selected polling stations collected data directly, feeding it into a Quick Count Database for real-time analysis, yielding consistent results with minimal variance. Unlike traditional exit polls, which suffer from delays in data processing, this methodology enabled immediate detection of anomalies, real-time adjustments for non-response bias, and continuous monitoring of voting patterns. This approach not only addressed issues of sampling bias but also provided an early warning system for electoral irregularities, contributing to improved electoral integrity in Ghana. The findings suggest that combining traditional exit polling with real-time analytics can significantly improve the timeliness and accuracy of election monitoring, potentially setting a new standard.

Real-Time Analytics Meets Traditional Exit Polling.

The Sampling Method utilized a combination of stratified sampling, cluster sampling, and simple random sampling.

This research represents a departure from traditional exit polling methods by employing a three-tier sampling approach that merges the immediacy of real-time data.

This innovation addressed a key limitation of conventional exit polling: the delay between data collection and results. It also used real data for its analysis.

Traditional exit polls primarily focus on voter demographics and political preferences, but this new methodology is designed to identify electoral irregularities. 

Government Statistics Section