Random Variables for Scientists and Engineers (Synthesis Lectures on Engineering, Science, and Technology) - Tapa dura

Acerca del autor

Rajan Chattamvelli, PhD, 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.

De la contraportada

This book provides an overview of random variables (RVs) and their applications.  The authors begin with mathematical expectation, cumulative distribution function, and functions of RVs, and some applications of conditional expectation follow.  The book then discusses transformations of RVs and a simple integral method to find the mean deviation of continuous RVs.  Joint probability distributions, do-little method of Jacobians, polar-transformations, Rosenblatt transform, copula-based methods, and its applications are covered.  An up-to-date reference list and approximately 225 exercise problems appear in the book. The authors have updated and expanded upon their writing on these topics, which they originally covered in a previous book, Statistics for Scientists and Engineers.

In addition, this book:

• Combines theory with numerical examples to provide a thorough explanation of the topic

• Includes numerous exercises so that readers can practice applying the concepts within the book

• Presents an up-to-date reference list and around 225 exercise problems