Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Faculty Publications- Book Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Rajesh, R.; El-Ashmawi, Walaa H.; Al Husaini, Yousuf Nasser Said; Shenoi, Jeevanand Edavazhikkal Sarvothama Title A name given to the resource Sustainable Innovations in Statistics and Data Science Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Sustainable Innovations in Statistics and Data Science;pp.1-360 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-1454-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-1454-9</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105032729920?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105032729920?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajesh R., Department of Statistics and Data Science, Christ University, India; El-Ashmawi W.H., Misr International University, Egypt; Al Husaini Y.N.S., Arab Open University, Oman; Shenoi J.E.S., Department of Statistics and Data Science, Christ University, India Description An account of the resource Description: 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. Coverage: The many academic areas covered in this publication include, but are not limited to: Air Pollution Artificial Intelligence (AI) Cardiovascular Health Climate Change Corporate Social Responsibility (CSR) Data Science Environmental Science Geometric Distribution Healthcare Quality Control Smart Cities Statistics Sustainable Innovation Urban Analytics Urban Development. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833731456-3; 979-833731454-9; Language A language of the resource English Type The nature or genre of the resource Book Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online