Introduction

In the high-stakes arena of political forecasting, the credibility of data is paramount. As Ghana prepares for the New Patriotic Party’s (NPP) 2026 presidential primaries scheduled for January 31, a new study has placed Kennedy Agyapong as the clear frontrunner. However, beyond the headline figures lies a rigorous methodological innovation: the use of fully automated, randomized sampling.

Dr. Evans Duah, an impartial researcher, chartered accountant, lecturer, and fiscal economist, spearheaded this study conducted between August 2025 and January 9, 2026. In an interview on The Pulse on JoyNews, Dr. Duah detailed how his team eliminated human interference to ensure that the data reflects genuine delegate sentiment rather than researcher bias. This article explores the mechanics of automated sampling, its application in the NPP delegate survey, and why this approach represents the future of political research in Ghana.

Key Points

Background

The New Patriotic Party (NPP) is set to elect its flagbearer for the upcoming general elections on January 31, 2026. With several prominent figures vying for the position, political analysts and researchers are closely monitoring delegate preferences. Historically, political polling in Ghana has relied on manual sampling methods, which involve researchers selecting respondents based on convenience or stratified plans. While effective, these methods can inadvertently introduce bias—whether through the researcher’s subconscious selection of “friendly” delegates or through logistical limitations that exclude certain demographics.

The Researcher

Dr. Evans Duah brings a multidisciplinary approach to political science. As a chartered accountant and fiscal economist, his expertise lies in data integrity and statistical accuracy. His decision to conduct a national study on the NPP primaries was driven by a need for empirical evidence amidst a crowded field of speculative reports.

The Study Timeline

The research was not a snapshot but a longitudinal study. Commencing in August 2025 and concluding on January 9, 2026, the five-month window allowed the team to track shifts in sentiment and verify data points over time, lending robustness to the final projections.

Analysis: The Science of Automated Sampling

At the heart of Dr. Duah’s study is the concept of automated sampling. This is defined as the use of mechanical programs to gather representative samples at set intervals without human intervention. In the context of the NPP delegate survey, this meant utilizing a system-driven investment to select individuals from a verified delegate population.

How Automated Sampling Works

Unlike traditional polling, where a field agent might physically visit a constituency and choose whom to interview, automated sampling relies on a digital database—in this case, the NPP’s “album” of delegates. The system uses algorithms to randomly select delegates from the pool of 204,893.

Dr. Duah explained, “The sampling was actually not manually done. It is entirely system-driven and totally randomised. There is no human interface, so nobody knows who is being called. We simply picked delegates from the database, and the system does the rest.”

Eliminating Human Bias

Bias in research can manifest in several ways:

• Selection Bias: Occurs when the sample is not representative of the population.
• Interviewer Bias: Occurs when the interviewer’s tone or demeanor influences the respondent’s answers.
• Convenience Sampling: Selecting delegates who are easily accessible rather than those who are statistically relevant.

By removing the human element, Dr. Duah’s methodology ensured that “nobody knows who is being called.” This anonymity is crucial. When delegates respond without the pressure of a face-to-face interaction with a human pollster, they are more likely to provide candid responses free from preconceptions or social desirability bias.

Proportional Representation

A critical aspect of the NPP delegate structure is the composition of the voting body. Dr. Duah noted that the delegate base consists of approximately 5.5% “super delegates”—comprising MPs, Council of Elders, and constituency executives—and 94% grassroots members.

Automated sampling excels in maintaining these ratios. The algorithm was programmed to ensure that the sample structure accurately mirrored the population structure. This prevents the common error where grassroots delegates (who are harder to reach) are underrepresented compared to party executives.

Practical Advice: Applying Automated Methodology

For researchers, political analysts, and organizations looking to replicate the credibility of Dr. Duah’s study, the following principles of automated sampling should be adopted.

1. Establish a Verified Database

Automation is only as good as the data it processes. The first step is to secure a comprehensive and verified list of the target population. In this case, the “album” of 204,893 delegates served as the master list. Without a clean database, automated systems cannot generate a representative sample.

2. Utilize Randomization Algorithms

Do not rely on manual selection. Use statistical software that employs random number generation or stratified random sampling algorithms. This ensures that every member of the population has an equal probability of selection (probability sampling).

3. Ensure Anonymity and Confidentiality

To get the most accurate sentiment, particularly in sensitive political environments, the data collection process must be confidential. Automated calls or digital surveys remove the interpersonal pressure that can skew results.

4. Validate the Sample Structure

After the automated system generates the sample, researchers must perform a post-stratification check. Verify that the sample demographics match the population demographics (e.g., the 5.5% vs. 94% split in the NPP study). If there is a discrepancy, the algorithm should be adjusted or weighted.

Frequently Asked Questions (FAQ)

What is automated sampling?

Automated sampling is a research method that uses computerized systems to randomly select participants from a database without human intervention. It is designed to enhance accuracy, efficiency, and consistency in data collection.

Why is automated sampling considered less biased than manual methods?

Manual sampling relies on human judgment, which can be influenced by convenience, personal relationships, or subconscious preferences. Automated sampling uses strict algorithms to ensure every individual has an equal chance of being selected, eliminating these human factors.

Who is Kennedy Agyapong?

Kennedy Agyapong is a prominent member of the New Patriotic Party (NPP) and a Member of Parliament for Assin Central. He is a leading aspirant in the party’s 2026 presidential primaries.

How many delegates are involved in the NPP primaries?

According to the study by Dr. Evans Duah, the verified delegate population for the 2026 primaries is 204,893.

What does “50% plus one” mean in this context?

For a candidate to win the NPP flagbearer race in a single round, they must secure more than half of the total valid votes cast. If there are 100 votes, a candidate needs 51 votes (50% + 1) to win outright.

Conclusion

The study conducted by Dr. Evans Duah offers more than just a snapshot of the NPP presidential primaries; it provides a blueprint for objective political research in Ghana. By leveraging automated sampling, the study removed the specter of human bias, delivering a clear, data-backed projection that Kennedy Agyapong currently holds a decisive advantage among delegates.

As the January 31 primaries approach, the reliance on system-driven, randomized methodologies will likely become the gold standard for polling. For political parties and the electorate, these advancements promise a future where electoral predictions are grounded in statistical reality rather than perception.