Communication Challenges, Errors, and Consequences

Key challenges in the communication of data and statistics are examined, emphasizing how methodological errors, misinterpretation, and the neglect of uncer- tainty, underlying assumptions, and inferential risks can distort evidence and mislead public understanding. Common pitfalls discussed include the mishandling of missing data, the overreliance on p-values and statistical significance, various forms of bias, and the blind use of Big Data and AI-driven analyses, whose scale may conceal rather than resolve data-quality and inferential issues. Responsible statistical communication and stronger statistical literacy emerge as essential to prevent misinformation and support informed decision-making in contemporary data-rich societies.