This book provides thorough and comprehensive coverage of most of the new and important quantitative methods of data analysis for graduate students and practitioners. In recent years, data analysis methods have exploded alongside advanced computing power, and it is critical to understand such methods to get the most out of data, and to extract signal from noise. The book excels in explaining difficult concepts through simple explanations and detailed explanatory illustrations. Most unique is the focus on confidence limits for power spectra and their proper interpretation, something rare or completely missing in other books. Likewise, there is a thorough discussion of how to assess uncertainty via use of Expectancy, and the easy to apply and understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes.
A comprehensive guide to quality improvement from the leading expert in information and data warehouse quality.Each year, companies lose millions as a result of inaccurate and missing data in their op
The authors contribute a dispassionate, independent, and objective comment that has been missing from media debate of the effects of Australia’s immigration policies. They provide a wealth of data on
Demonstrates how to become adjusted to the Macintosh operating system and how to transfer data from a Windows system to a Macintosh, discussing topics such as moving files and Macintosh equivalents to
A Canadian astronomer commits suicide on a desolate mountain peak in Hawaii, and Morgan O'Brien is sent to the observatory to find his missing data. But it seems she's not the only one who needs those
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
Apply a fully test-driven approach to machine-learning algorithms, and save yourself the pain of missing mistakes in your analyses. Most data scientists have run an analysis and simply accepted any an
This book introduces Converse of Bayes’ Theorem and demonstrates its unexpected applications and points to possible future applications, such as, solving the Bayesian Missing Data Problem (MDP) when t
Paleontologists and geologists struggle with research questions often complicated by the loss or even absence of key paleobiological and paleoenvironmental information. Insight into this missing data
John David Anderson returns with the conclusion to the epic coming-of-age adventure that began in Stowaway―a riveting and heartfelt search for hope and home, family and future, in a galaxy ravaged by war.Leo Fender is no stranger to catastrophe, whether it’s the intergalactic war that took his mother’s life or the ongoing fight for his own. He’s seen his planet plundered, his ship attacked, his father kidnapped, and his brother go missing―and found himself stranded on a ship with a bunch of mercenary space pirates. Still, nothing could have prepared him for the moment he and the crew tried to save his father―and discovered a dark plot that could destroy hundreds of worlds in the blink of an eye.Now, Leo is adrift. His father has sent him on a mission with nothing but a data chip and a name of someone who could help, and Captain Bastian Black and the crew of the Icarus are determined to see this through to the end with Leo, to fulfill his father’s wish and prevent further conflict. But
How a web-scale network of autonomous micromanagers can challenge the AI revolution and combat the high cost of quantitative business optimization.The artificial intelligence (AI) revolution is leaving behind small businesses and organizations that cannot afford in-house teams of data scientists. In Microprediction, Peter Cotton examines the repeated quantitative tasks that drive business optimization from the perspectives of economics, statistics, decision making under uncertainty, and privacy concerns. He asks what things currently described as AI are not “microprediction,” whether microprediction is an individual or collective activity, and how we can produce and distribute high-quality microprediction at low cost. The world is missing a public utility, he concludes, while companies are missing an important strategic approach that would enable them to benefit―and also give back. In an engaging, colloquial style, Cotton argues that market-inspired “superminds” are likely to be very e
Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, the authors focus on the inference methods rooted in statistical physics and information theory. The discussion is organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections.
During the past half-century, exponential families have attained a position at the center of parametric statistical inference. Theoretical advances have been matched, and more than matched, in the world of applications, where logistic regression by itself has become the go-to methodology in medical statistics, computer-based prediction algorithms, and the social sciences. This book is based on a one-semester graduate course for first year Ph.D. and advanced master's students. After presenting the basic structure of univariate and multivariate exponential families, their application to generalized linear models including logistic and Poisson regression is described in detail, emphasizing geometrical ideas, computational practice, and the analogy with ordinary linear regression. Connections are made with a variety of current statistical methodologies: missing data, survival analysis and proportional hazards, false discovery rates, bootstrapping, and empirical Bayes analysis. The book con
A textbook that uses a hands-on approach to teach principles of programming languages, with Java as the implementation language.This introductory textbook teaches the principles of programming languages by using an experiential learning style, in which students learn about language features by realizing those features in a pedagogical compiler. Students use Java―the most commonly used programming language in the first two years of the computer science curriculum―as the implementation language throughout. The book also discusses a range of emerging topics in programming languages missing from existing textbooks, including concurrency, Big Data, and event-driven programming. The goal is to prepare students to design, implement, analyze, and understand both domain-specific and general-purpose programming languages. The book first develops basic concepts in languages, including means of computation using primitive values, means of combination such as variable definition and functions, an
In the nineteenth and early twentieth centuries, modern states began to provide many of the public services we now take for granted. Inward Conquest presents the first comprehensive analysis of the political origins of modern public services during this period. Ansell and Lindvall show how struggles among political parties and religious groups shaped the structure of diverse yet crucially important public services, including policing, schooling, and public health. Liberals, Catholics, conservatives, socialists, and fascists all fought bitterly over both the provision and political control of public services, with profound consequences for contemporary political developments. Integrating data on the historical development of public order, education, and public health with novel measures on the ideological orientation of governments, the authors provide a wealth of new evidence on a missing link in the history of the modern state.
In the nineteenth and early twentieth centuries, modern states began to provide many of the public services we now take for granted. Inward Conquest presents the first comprehensive analysis of the political origins of modern public services during this period. Ansell and Lindvall show how struggles among political parties and religious groups shaped the structure of diverse yet crucially important public services, including policing, schooling, and public health. Liberals, Catholics, conservatives, socialists, and fascists all fought bitterly over both the provision and political control of public services, with profound consequences for contemporary political developments. Integrating data on the historical development of public order, education, and public health with novel measures on the ideological orientation of governments, the authors provide a wealth of new evidence on a missing link in the history of the modern state.
This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component d
DNA ancestry companies generate revenues in the region of $1bn a year, and the company 23andMe is said to have sold 10 million DNA ancestry kits to date. Although evidently popular, the science behind how DNA ancestry tests work is mystifying and difficult for the general public to interpret and understand. In this accessible and engaging book, Sheldon Krimsky, a leading researcher, investigates the methods that different companies use for DNA ancestry testing. He also discusses what the tests are used for, from their application in criminal investigations to discovering missing relatives. With a lack of transparency from companies in sharing their data, absent validation of methods by independent scientists, and currently no agreed-upon standards of accuracy, this book also examines the ethical issues behind genetic genealogy testing, including concerns surrounding data privacy and security. It demystifies the art and science of DNA ancestry testing for the general reader.
We all rely on charts to navigate at sea – but are we missing essential information? A mass of data is included on each chart and deciphering the many symbols and abbreviations can be complicated. The
Models and likelihood are the backbone of modern statistics. This 2003 book gives an integrated development of these topics that blends theory and practice, intended for advanced undergraduate and graduate students, researchers and practitioners. Its breadth is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics such as likelihood and linear and generalized linear models. Each chapter contains a wide range of problems and exercises. Practicals in the S language designed to build computing and data analysis skills, and a library of data sets to accompany the book, are available over the Web.
