Mathematics

Integrative Approaches to Quality, Data Analysis, and Interdisciplinary Research
Editors: Amir Ahmad Dar, PhD
Waseem Z. Loan, PhD

Integrative Approaches to Quality, Data Analysis, and Interdisciplinary Research

In Production
Pub Date: Forthcoming November 2025
Hardback Price: $180 US | £150 UK
Hard ISBN: 9781779641007
Pages: Est. 278pp w/index
Binding Type: Hardback / ebook
Notes: 10 color and 53 b/w illustrations

In a world increasingly driven by data and precision, this new book, Integrative Approaches to Quality, Data Analysis, and Interdisciplinary Research, comprehensively explores advanced methodologies and their applications across various domains, offering a holistic approach to problem-solving and dismantling conventional barriers. It helps to bridge the gap between theory and practice and presents insights covering quality management, risk assessment, environmental analysis, and more.

Emphasizing cross-disciplinary approaches, the chapters highlight many methods and applications for data analysis and interdisciplinary research, including various statistical methods, CUSUM (Cumulative Sum) control charts, Poisson distribution models, the Bayesian approach, software programs like Mathematica,
machine learning algorithms, big data, and more. The book focuses on the transformative power of data analysis in addressing complex challenges in many areas, including for environmental problems, such as measuring air pollution; in socioeconomic issues, like insurance costs and dynamics; in healthcare, such as for analyzing epidemiological data (such as from the COVID-19 pandemic); in the agricultural sector, such as to understand and forecast agricultural trends and to enhance agricultural sustainability; and more.

Offering a wide range of case studies, the volume highlights the practical applications of integrating quality management, data analysis, and multidisciplinary research, from solving urgent environmental challenges to improving public health and company operations. By bridging the gap between theory and practice, it emphasizes the transformative power of data and interdisciplinary approaches in addressing complex challenges and driving innovation.

CONTENTS:
Preface

Introduction

PART I: DATA-DRIVEN ANALYSIS IN VARIOUS SECTORS

1. Machine Learning Algorithms for Covid-19 Data Analysis with Python

Tashi Lhamo and Geeta Arora

2. Analysis of Air Pollution in Delhi Using Machine Learning Techniques
Hrithik Pm and Mohit Nain

3. Modeling Socioeconomic and Regional Factors in the Non-Life Insurance Sector of India Through Regression Analysis
Akshat Jain, Rakesh Malhan, and Imran Azad

4. Quantitative Analysis of Healthcare Costs: Integrating Behavioral, Regional, and Demographic Factors
Mehak Malhotra, Rakesh Malhan, and Ataur Rahman Farooqi

5. A Time-Series Analysis of Lemon Production in Ten Major Cities of India
Anil Kumar, Mohit Nain, and Amit Kumar Pathak

PART II: INTERDISCIPLINARY STUDIES IN AGRICULTURE, EDUCATION, AND HISTORY
6. Optimizing Water Management for Sustainable Agriculture: A Multidisciplinary Approach

Preety Kalra, Nisha, Navdeep Kaur, and Tasneem Shah

7. Factor Analysis for Attention Deficit Hyperactivity Disorder Symptoms Questionnaires (Adult ADHD Self-Report Scale V1.1) Among HEI Learners
Sachitanand Singh, Renu Thakur, and Krishan Kumar

8. History of Mathematics in Africa, from Ancient Mathematics to Modern Data Science: Africa Legacy and Future
Arshad Ahmad Khan, Sani Haliru Rini, Yakubu Ibrahim Barga, Bashar Suleiman Argungu, and Abbas Yusuf Balarabe

9. Exploring Decentralized Inventory Strategies: A Study
Nitin Kumar Mishra, Prerna Jain, Renuka Namwad, and Ranu

PART III: ADVANCED TECHNIQUES IN QUALITY AND RISK MANAGEMENT

10. Advancing Quality Management: Exploring the Power of CUSUM (Cumulative Sum) Control Charts in Process Monitoring and Improvement

Manzoor Ahmad Khanday, Chukka Sowjanya, and Mohammad Shahfaraz Khan

11. Premium Precision: A Bayesian Approach Using Poisson and Exponential Models in Insurance Risk Assessment
Avneet Kaur Chahal, Rakesh Kumar, and Olayan Albalawi

12. Optimizing Supply Chain Efficiency with Mathematica: Mathematical and Statistical Methods for Finite Planning Horizons
Ranu, Nitin Kumar Mishra, Renuka S. Namwad, Jatoth Heeraman, and Prerna Jain


Index


About the Authors / Editors:
Editors: Amir Ahmad Dar, PhD
Assistant Professor, Department of Statistics, Lovely Professional University, India

Amir Ahmad Dar, PhD, is currently serving as an Assistant Professor in the Department of Statistics at Lovely Professional University in India. Dr. Dar has an impressive academic portfolio, having published over 20 research papers and 10 book chapters. He has presented his work at eight national and international conferences. His research interests include actuarial statistics, experimental design, financial derivatives, and financial mathematics. He completed his BSc in Actuarial and Financial Mathematics at the Islamic University of Science and Technology in Awantipora, India. He pursued his MSc and PhD in Actuarial Science at B S Abdur Rahman University in Chennai, India.

Waseem Z. Loan, PhD
Research Associate, Indian Institute of Technology, Patna, India

Waseem Z. Lone, PhD, is currently a Research Associate at the Indian Institute of Technology, Patna, India. His research focuses on Fourier and wavelet analysis. He has published over 20 papers in various esteemed international journals. Dr. Waseem has also served as an Assistant Professor at Lovely Professional University, Punjab, India, and has been awarded a prestigious fellowship funded by the Council of Scientific & Industrial Research (CSIR), Government of India. He earned a master degree from the University of Kashmir, India. He also completed his PhD in Mathematics at the same university.




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