Welcome to our book review site www.go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Introduction to Probability and Statistics for Data Science
Introduction to Probability and Statistics for Data Science provides a solid course in the fundamental concepts, methods and theory of statistics for students in statistics, data science, biostatistics, engineering, and physical science programs. It teaches students to understand, use, and build on modern statistical techniques for complex problems. The authors develop the methods from both an intuitive and mathematical angle, illustrating with simple examples how and why the methods work. More complicated examples, many of which incorporate data and code in R, show how the method is used in practice. Through this guidance, students get the big picture about how statistics works and can be applied. This text covers more modern topics such as regression trees, large scale hypothesis testing, bootstrapping, MCMC, time series, and fewer theoretical topics like the Cramer-Rao lower bound and the Rao-Blackwell theorem. It features more than 250 high-quality figures, 180 of which involve actual data. Data and R are code available on our website so that students can reproduce the examples and do hands-on exercises.
Analytic Methods in Systems and Software Testing
A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regr...
Intelligent Transportation Related Complex Systems and Sensors
Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, sm...
Innovative Statistical Methods for Public Health Data
The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.
The Best Writing on Mathematics 2021
The year’s finest mathematical writing from around the world This annual anthology brings together the year’s finest mathematics writing from around the world—and you don’t need to be a mathematician to enjoy the pieces collected here. These essays—from leading names and fresh new voices—delve into the history, philosophy, teaching, and everyday aspects of math, offering surprising insights into its nature, meaning, and practice, and taking readers behind the scenes of today’s hottest mathematical debates. Here, Viktor Blåsjö gives a brief history of “lockdown mathematics”; Yelda Nasifoglu decodes the politics of a seventeenth-century play in which the characters are geometric shapes; and Andrew Lewis-Pye explains the basic algorithmic rules and computational procedures behind cryptocurrencies. In other essays, Terence Tao candidly recalls the adventures and misadventures of growing up to become a leading mathematician; Natalie Wolchover shows how old math gives new clues about whether time really flows; and David Hand discusses the problem of “dark data”—information that is missing or ignored. And there is much, much more.
Mathematical Statistics with Applications
This is the most widely used mathematical statistics text at the top 200 universities in the United States. Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid undergraduate foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research.
ICOIN the 15th
"IEEE Computer Society Order Number PR00951"--Verso of t.p.
