ABSTRACT Statistical analysis plays a critical role in biomedical research, ensuring that data are interpreted appropriately and that conclusions are both valid and reproducible. In allergy and immunology, where studies increasingly rely on complex data structures and analytical approaches, clarity on biostatistical methods is essential to support transparency and scientific rigor. However, inconsistent statistical reporting and misuse of analytical techniques remain persistent challenges in the field. This review provides a structured and practice‐oriented overview of key statistical aspects relevant to research in allergy and immunology Drawing upon recent peer‐reviewed articles in these disciplines, we highlight best practices in the transparent reporting of statistical methods, verification of underlying assumptions, and interpretation of statistical significance in the context of clinical relevance. Each section is illustrated with practical examples to demonstrate sound analytical reasoning and to guide researchers, reviewers, and educators in improving statistical standards across the field.
Ordak et al. (Sat,) studied this question.