Sustainable innovations in statistics and data science are increasingly vital in tackling complex global challenges such as climate change, public health crises, and resource management. By developing and applying advanced analytical methods, these fields enable more efficient, equitable, and informed decision-making across sectors. Integrating sustainability into data practices ensures that technologies support long-term environmental, social, and economic goals. This intersection not only enhances the accuracy and relevance of insights but also promotes ethical data use aligned with global sustainability standards. Sustainable Innovations in Statistics and Data Science brings together cutting-edge research, methodologies, and applications that address sustainability challenges across various fields. It delves into insights, techniques, and case studies that drive sustainable outcomes in environmental science, healthcare, urban planning, and other critical areas. Covering topics such as air pollution, environmental science, and urban development, this book is an excellent resource for researchers, academicians, graduate and postgraduate students, data science and statistics practitioners, policymakers, government officials, industry leaders, innovators, educators, curriculum developers, and more.
