Ethics in Biostatistics and Data Science Research and Practice

This interactive course encompasses traditional elements of responsible conduct of research training, best practices in data management and analysis, and ethical issues encountered during the development and application of biostatistical and data science methods. Topics covered include research misconduct, protection of human subjects, data management, reproducibility of research, authorship, collaboration, conflicts of interest and commitment, peer review, and healthy mentoring relationships, with accompanying case studies relevant to the data science field. Emerging issues in clinical trials, data science, and artificial intelligence will be discussed. Guidelines published by professional organizations composed of statisticians and data scientists will be reviewed. Class sessions will consist of a traditional lecture portion where concepts and definitions are explained, followed by one or more case study discussions.