Statistics for Scientists and Engineers download ebook EPUB, TXT, DOC
9781118228968 English 1118228960 Covering descriptive statistics with an emphasis on scientific and engineering applications, 'Statistics for Scientists and Engineers' brings to light new programming ideas, algorithms, and equations. Providing insight on coding complex algorithms using the 'loop unrolling technique, ' author R, One of the key uses of descriptive statistics is to summarize data, rather than use the data to learn about the population that the data represents. This important reference offers scientists and engineers an introduction to descriptive statistics with an emphasis on scientific and engineering applications. The book provides a thorough introduction to data scales, data transformations and popular data discretization techniques as well as sampling distributions, joint and conditional distributions, statistical quality control, reliability analysis and failure modes. The book includes data sets, illustrative examples, end-of-chapter exercises as well as new algorithms and equations not available anywhere else., Provides insight on coding complex algorithms using the "loop unrolling technique" Covers dynamic data dependent systems such as industrial robots, unmanned aerial vehicles (UAV) and pilot-less machines Contains extensive exercises at the end of each chapter and examples from inter-disciplinary fields, Provides the theoretical framework needed to build, analyzeand interpret various statistical models. It helps readers choosethe correct model, distinguish among various choices that bestcaptures the data, or solve the problem at hand. This is an introductory textbook on probability and statistics.The authors explain theoretical concepts in a stepbystep mannerand provide practical examples. This book begins with anintroductory chapter that presents the basic concepts. Next, theauthors discuss the measures of location, popular measures ofspread, and measures of skewness and kurtosis. Probability theory,discrete distributions, and important continuous distributions thatare often encountered in practical applications are analyzed.Mathematical Expectation is covered, along with generatingfunctions and Functions of Random Variables. This book discussesjoint distributions, Estimation, Regression, and Analysis ofvariance. Statistical Quality Control and reliability analysis arealso presented. Provides insight on coding complex algorithms using the "loopunrolling technique" Covers dynamic data dependent systems such as industrialrobots, unmanned aerial vehicles (UAV) and pilotless machines Contains extensive exercises at the end of each chapter andexamples from interdisciplinary fields Statistics for Scientists and Engineers is a great resourcefor students in engineering, physical sciences, and management, andalso practicing engineers who require skill sets to model practicalproblems in a statistical setting., This book provides the theoretical framework needed to build, analyze and interpret various statistical models. It helps readers choose the correct model, distinguish among various choices that best captures the data, or solve the problem at hand. This is an introductory textbook on probability and statistics. The authors explain theoretical concepts in a step-by-step manner and provide practical examples. The introductory chapter in this book presents the basic concepts. Next, the authors discuss the measures of location, popular measures of spread, and measures of skewness and kurtosis. Probability theory, discrete distributions, and important continuous distributions that are often encountered in practical applications are analyzed. Mathematical Expectation is covered, along with Generating Functions and Functions of Random Variables. It discusses joint distributions, and novel methods to find the mean deviation of discrete and continuous statistical distributions. Provides insight on coding complex algorithms using the 'loop unrolling technique' Covers illuminating discussions on Poisson limit theorem, central limit theorem, mean deviation generating functions, CDF generating function and extensive summary tables Contains extensive exercises at the end of each chapter and examples from interdisciplinary fields Statistics for Scientists and Engineers is a great resource for students in engineering, physical sciences, and management, and also practicing engineers who require skill sets to model practical problems in a statistical setting.
9781118228968 English 1118228960 Covering descriptive statistics with an emphasis on scientific and engineering applications, 'Statistics for Scientists and Engineers' brings to light new programming ideas, algorithms, and equations. Providing insight on coding complex algorithms using the 'loop unrolling technique, ' author R, One of the key uses of descriptive statistics is to summarize data, rather than use the data to learn about the population that the data represents. This important reference offers scientists and engineers an introduction to descriptive statistics with an emphasis on scientific and engineering applications. The book provides a thorough introduction to data scales, data transformations and popular data discretization techniques as well as sampling distributions, joint and conditional distributions, statistical quality control, reliability analysis and failure modes. The book includes data sets, illustrative examples, end-of-chapter exercises as well as new algorithms and equations not available anywhere else., Provides insight on coding complex algorithms using the "loop unrolling technique" Covers dynamic data dependent systems such as industrial robots, unmanned aerial vehicles (UAV) and pilot-less machines Contains extensive exercises at the end of each chapter and examples from inter-disciplinary fields, Provides the theoretical framework needed to build, analyzeand interpret various statistical models. It helps readers choosethe correct model, distinguish among various choices that bestcaptures the data, or solve the problem at hand. This is an introductory textbook on probability and statistics.The authors explain theoretical concepts in a stepbystep mannerand provide practical examples. This book begins with anintroductory chapter that presents the basic concepts. Next, theauthors discuss the measures of location, popular measures ofspread, and measures of skewness and kurtosis. Probability theory,discrete distributions, and important continuous distributions thatare often encountered in practical applications are analyzed.Mathematical Expectation is covered, along with generatingfunctions and Functions of Random Variables. This book discussesjoint distributions, Estimation, Regression, and Analysis ofvariance. Statistical Quality Control and reliability analysis arealso presented. Provides insight on coding complex algorithms using the "loopunrolling technique" Covers dynamic data dependent systems such as industrialrobots, unmanned aerial vehicles (UAV) and pilotless machines Contains extensive exercises at the end of each chapter andexamples from interdisciplinary fields Statistics for Scientists and Engineers is a great resourcefor students in engineering, physical sciences, and management, andalso practicing engineers who require skill sets to model practicalproblems in a statistical setting., This book provides the theoretical framework needed to build, analyze and interpret various statistical models. It helps readers choose the correct model, distinguish among various choices that best captures the data, or solve the problem at hand. This is an introductory textbook on probability and statistics. The authors explain theoretical concepts in a step-by-step manner and provide practical examples. The introductory chapter in this book presents the basic concepts. Next, the authors discuss the measures of location, popular measures of spread, and measures of skewness and kurtosis. Probability theory, discrete distributions, and important continuous distributions that are often encountered in practical applications are analyzed. Mathematical Expectation is covered, along with Generating Functions and Functions of Random Variables. It discusses joint distributions, and novel methods to find the mean deviation of discrete and continuous statistical distributions. Provides insight on coding complex algorithms using the 'loop unrolling technique' Covers illuminating discussions on Poisson limit theorem, central limit theorem, mean deviation generating functions, CDF generating function and extensive summary tables Contains extensive exercises at the end of each chapter and examples from interdisciplinary fields Statistics for Scientists and Engineers is a great resource for students in engineering, physical sciences, and management, and also practicing engineers who require skill sets to model practical problems in a statistical setting.