This paper provides a comprehensive exploration of the role and significance of basic statistics in educational research. Drawing upon historical foundations and theoretical frameworks, the study elucidates the evolution of statistical methodologies and their application in understanding complex educational phenomena. Key pioneers such as Francis Galton and Karl Pearson are highlighted for their foundational contributions, laying the groundwork for statistical analysis in education. The paper examines various statistical techniques, including descriptive and inferential statistics, correlation analysis, regression analysis, and analysis of variance (ANOVA), showcasing their relevance in analyzing diverse aspects of teaching, learning, and educational outcomes. Moreover, the integration of statistical methodologies into educational research is examined across domains such as educational management, policy-making, and teaching practice, emphasizing their role in informed decision-making, resource allocation, and policy formulation. Despite the benefits, challenges such as sample bias and misapplication of statistical tests are acknowledged, underscoring the importance of methodological rigor and statistical literacy among researchers and practitioners. Looking ahead, the paper discusses future directions in educational research, including the integration of advanced statistical techniques and efforts to promote statistical literacy. Overall, this paper offers a comprehensive framework for understanding the complexities of basic statistics in educational research, highlighting its transformative potential in driving positive change and innovation within the education sector.
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