Statistical Methods and Applications in Systems Assurance and Quality

In the era of big data and real-time monitoring, vast amounts of information are generated every second through sensors and advanced tracking systems. The information contained in the data needs to be carefully analyzed and accurate results must be delivered to the users as soon as possible. This book explores the critical role of statistics in modern technologies and applied sciences such as health, informatics, and production systems. Statistical Methods and Applications in Systems Assurance and Quality provides a comprehensive overview of statistical methods for ensuring system quality and reliability. It discusses best practices for improving the quality of manufacturing products by using proper statistical methods. The book covers the current state of statistical methods used for system quality and conveys the importance of healthcare systems and employing statistics in the detection of epidemic outbreaks. Designed for researchers, industry professionals, and academics, this reference is ideal for those working in manufacturing, healthcare, computer engineering, statistical process control, and machine learning applications. It serves as a valuable resource for anyone seeking to enhance system performance through data-driven insights.

Dr. Sotiris Bersimis is a Professor at the University of Piraeus, Department of Business Administration and an elected member of International Statistical Institute. He is a PhD holder in Statistics, from the Statistics and Insurance Science Department of the University of Piraeus. He also holds an MSc in Statistics from Athens University of Economics and Business and a BSc in Statistics and Insurance Science from the University of Piraeus. His research interests are mostly related to the development and implementation of stochastic models for processes monitoring (processes' quality control, patients' surveillance, quality of services, etc.), as well as with the theory of runs and patterns. He also works in the fields of data analytics and statistical machine learning. He has published more than 70 papers in international scientific while more than 120 of his papers have been presented in National (Greek) and International Conferences. In the past, during the period 9/2020-4/2022 he served as the Chair of the Department of Statistics and Insurance Science and as a member of the Senate of the University of Piraeus. In addition, during the period 12/2015-1/2019 he served as the President of the Hellenic Organization for Health Care Services Provision while during the period 4/2018-1/2019 he has been elected and served as the president of European Healthcare Fraud & Corruption Network (EHFCN). Dr. Polychronis Economou is an Associate Professor in the Department of Civil Engineering at the University of Patras, Greece. He earned a BSc in Mathematics from the University of Ioannina in 2001 and an MSc in Applied Mathematics from the National Technical University of Athens (NTUA) in 2003. In 2007, he completed his doctoral thesis, Heterogeneity Models in Lifetime Data Analysis, also at NTUA. Dr. Economou's research spans several areas of applied statistics, including Survival and Reliability Models, Diagnostic Tests, Statistical Process Control and Monitoring, and Biased Sampling and Weighted Distributions. His work is characterized by methodological rigor and practical applications, often addressing complex real-world problems. He has contributed significantly to the field, with over 75 articles published in international peer-reviewed journals and conference proceedings, earning widespread recognition for their impact. Additionally, he has co-authored four books, providing valuable resources for students and researchers in applied statistics. Dr. Economou actively collaborates with academic and industry partners, reflecting his commitment to advancing both theoretical and applied aspects of his research areas. He serves as an associate editor for three prestigious scientific journals specializing in statistics, further highlighting his standing in the academic community. Beyond his research and editorial responsibilities, Dr. Economou is an experienced educator, dedicated to mentoring students and guiding them in the development of statistical expertise to address contemporary challenges. Dr. Athanasios Rakitzis is an Assistant Professor in the Department of Statistics and Insurance Science at the University of Piraeus, in Greece. He holds a BSc in Mathematics from the National and Kapodestrian University of Athens, Greece and a MSc in Applied Statistics from the University of Piraeus, Greece. In 2008 he obtained his PhD in Statistics from the same department. He has served as a visiting professor (Lecturer) in the Department of Mathematics and Statistics, University of Cyprus, Cyprus, as an Assistant Professor at the Department of Statistics and Actuarial Mathematics, University of Aegean, Greece while he has also worked as a Post-doctoral researcher (Marie Curie Fellow) at the Université de Nantes, Institute Universitaire de Technologie de Nantes, France. He has published more than 70 research articles in international peer-review journals and conference proceedings and is the co-author of 2 books. He has participated, with announcement, in more than 100 National (Greek) and International Conferences. Also, he has supervised 2 PhD students in pursuing their PhD degree and 40 MSc theses. His research interests include statistical process control/monitoring and applied probability. Finally, he is a member of the Greek Statistical Institute and the European Network of Business and Industrial Statistics (ENBIS).

Section I: Statistical Quality Control Methods in Systems Assurance. 1. Stein EWMA Control Charts for Count Processes. 2. Time-varying ARMA Models for Residual Control Charts. 3. The Unconditional Performance of Control Charts for Zero-Inflated Processes with Estimated Parameters. 4. A Comparative Study of Self-starting CUSUM Control Charts for Location Shifts. Section II: Statistical Methods in Healthcare Systems Assurance. 5. Capturing Responder Effects in Randomized Clinical Trials with a Mixture Model. 6. Polygenic risk scores and applications in clinical practice. 7. Improving Healthcare Services using Machine Learning Techniques. 8. Health Budgets using Data Analytical Techniques. Section III: Statistical Methods in Sports and Industrial Systems Assurance. 9. Statistics and Machine Learning in Industry: Combining Heterogeneous or Multi-Scale Model Outputs. 10. The Value of Data Exploitation in Sports Industry: An Overview. 11. A New Approach to Basketball Game Predictions by Simulating Games Based on the Predicted Numbers and Types of Plays. Section IV: Miscellaneous Applications of Statistical Methods in Systems Assurance. 12. New Exponential Dispersion Models for Count Data - a Review and Applications. 13. Data Transformations and Transfer Functions: An Application to Water and Soil Pollution.