Synthesis Lectures on Engineering, Science, and Technology Random Variables for Scientists Engineers
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This book provides an introductory overview of random variables and their transformations. 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. 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 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.
This book provides an introductory overview of random variables and their transformations. 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. 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 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.
AmazonPages: 164, Edition: 2024, Hardcover, Springer
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