Quantitative and Qualitative Methods for Screening Scientific Grant Projects and Applications
Ixebayeva Z. Bagisov Z. Abulkassova D. Khamzina A. Iskaliyeva A.
19 November 2025International Academic Press
Statistics, Optimization and Information Computing
2025#14Issue 63741 - 3760 pp.
This article explores different methodological approaches to evaluating scientific grant applications and projects, focusing on the combination of quantitative and qualitative methods. Regression analysis, Bayesian networks, and multi-criteria evaluation are examined as complementary techniques within an integrated analytical framework. The study demonstrates how these methods can be applied to identify relationships, model uncertainty, and support structured decision-making in grant evaluation. Using both synthetic and empirical data, the models are tested and compared in terms of interpretability, predictive capacity, and transparency. The findings suggest that combining these approaches has strong potential to improve the fairness, consistency, and efficiency of funding allocation when applied under appropriate conditions. Rather than claiming proven effectiveness, this work illustrates the methodological viability and adaptability of such techniques for future research management and evaluation systems. Copyright
Bayesian Networks , Multi-Criteria Evaluation , Regression Analysis , Sampling Metrics , Scientific Research , Testing
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Faculty of Physics and Mathematics, Makhambet Utemisov West Kazakhstan University, Uralsk, Kazakhstan
Faculty of Physics and Mathematics
10 лет помогаем публиковать статьи Международный издатель
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