Distribution Theory

Fozia Homa, PhD, is Assistant Professor and Scientist in the Department of Statistics, Mathematics and Computer Application, Bihar Agricultural University, Sabour, India, and author or co-author of several journal articles. She has been a member of the organizing committees of several national and international seminars, conferences, and summits. Dr. Homa has received numerous awards for her research and teaching achievements from several organizations of national and international repute. Her areas of specialization include sample surveys, population studies, and mathematical modeling. Mukti Khetan, PhD, is Assistant Professor in the Department of Mathematics, Amity School of Applied Sciences, Amity University Mumbai, Maharashtra, India. She has more than four years of teaching and research experience. She formerly worked in the Department of Mathematics at IIT Bombay, Maharashtra, and in the Department of Statistics at Sambalpur University, Sambalpur, India. She has published research papers and book chapters. Mohd. Arshad, PhD, is an Assistant Professor in the Department of Mathematics at the Indian Institute of Technology Indore, India. He previously worked in the Department of Statistics and Operations Research at Aligarh Muslim University, India. He has published several research papers in international journals and is a member of editorial boards of various journals and scientific societies. He is also an author of the book Solutions to IIT JAM for Mathematical Statistics. Pradeep Mishra, PhD, is an Assistant Professor of Statistics at the College of Agriculture at the Jawaharlal Nehru Agricultural University, Jabalpur, Madhya Pradesh, India. He was previously a data management specialist at a private multinational company for several years. He specializes in the field of time series, design of experiments, and agriculture statistics. He has published more than 45 research articles in international and national journals and has received several awards for his work.

1. Descriptive Statistics: Principles and Applications 2. Random Variables and Their Properties 3. Discrete Distributions 4. Continuous Distributions 5. Family of Weibull Distributions 6. Life Distributions 7. Dynamics of Data Analysis and Visualization with Python