Data Analysis Errors and Limitations in Educational Research

Abstract

This study examines the statistical challenges faced by graduate students and faculty in educational and psychological research, employing a quantitative, cross-sectional survey design. Data was collected from 165 participants in Egyptian Colleges of Education using a newly developed 40-item questionnaire, which underwent expert review and reliability testing, with Cronbach's alpha coefficients ranging from 0.766 to 0.836. Findings indicate that IBM SPSS is the most popular statistical software, followed by STATA and R. Participants frequently reported issues such as the misuse of statistical methods, improper handling of missing data, over-reliance on significance testing without considering effect size, and inadequate interpretation of numerical results. The analysis also identified errors in assumptions related to parametric and non-parametric methods, which often led to misleading findings. Additionally, self-report biases and the tendency to omit study limitations were noted as critical factors affecting research integrity. Open-ended responses highlighted a reliance on statistical intermediaries due to limited expertise among researchers. The study underscores the need for enhanced statistical training and greater awareness of proper data management techniques in psychological and educational research, intending to improve research rigor and reliability. Survey, exploratory, and descriptive studies emerged as the most popular research types, reflecting a preference for observational and descriptive data over experimental designs.

Keywords: higher education, college readiness, data management, research reliability.