This book provides an introductory overview of random variables and their transformations. The authors approach the topic with statistics students in mind, along with researchers in various fields who are interested in data analysis. The book begins with by defining and explaining mathematical expectation. The authors then discuss transformations of random variables, including distribution functions and special functions. The book also covers joint probability distribution and its applications. The authors have updated and expanded upon their writing on these topics, which they originally covered in their previous book, Statistics for Scientists and Engineers.
Table des matières
Mathematical Expectation.- Functions of Random Variables.- Joint and Conditional Distributions.
A propos de l’auteur
Rajan Chattamvelli, Ph D, is a Professor in the School of Computer Science and Engineering at Amrita University, Amaravati. He has published more than 20 research articles in international journals of repute and at various conferences. His research interests are in computational statistics, design of algorithms, parallel computing, cryptography, data mining, machine learning, combinatorics, and big data analytics. His prior assignments include Denver Public Health, Colorado; Metromail Corporation, Lincoln, Nebraska; Frederick University, Cyprus; Indian Institute of Management; Periyar Maniammai University, Thanjavur; Presidency University, Bangalore, and VIT University, Vellore.Ramalingam Shanmugam, Ph.D., is an Honorary Professor in the School of Health Administration at Texas State University, San Marcos. He is the Editor-in-Chief of four journals including Advances in Life Sciences; Global Journal of Research and Review; Journal of Obesity and Metabolism; and the International Journal of Research in Medical Sciences. He has published more than 200 research articles and 120 conference papers. Dr. Shanmugam’s research interests include theoretical and computational statistics, number theory, operations research, biostatistics, decision making, and epidemiology.
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