Statistical Deception and Epistemic Responsibility: Mechanisms, Impacts, and Mitigation Strategies for Data Consumers

Abstract

Statistics play a central role in knowledge production, public policy, scientific research, and media communication. Their perceived objectivity grants them substantial persuasive authority, yet this same authority renders them susceptible to misuse and deception. This study examines how statistics are used to mislead audiences through selective data practices, inappropriate measures, model manipulation, and misleading visualisation. Drawing on statistical theory, cognitive psychology, and sociology of knowledge, the paper further explores how consumers of data can reduce vulnerability to deception. Emphasis is placed on statistical literacy, critical evaluation practices, transparency norms, and epistemic humility. The study contributes to methodological and policy-oriented debates by reframing statistical integrity as a shared responsibility between data producers and data consumers. The practical implications are outlined for education, research governance, media practice, and evidence-based policymaking.