Dear Data

The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail.

This book explores the use of integrated administrative data to understand and address the significant public health problem of child maltreatment. It examines the use of linked, or integrated, administrative data to increase understanding of population-level needs – and to inform decision-making efforts – within the child welfare system and across other public systems. The book details the technological innovations that have allowed for the accumulation and centralization of large datasets critical to identifying risks of child maltreatment and its negative consequences and to target community and system responses more accurately to address these challenges. Leading experts from the fields of child maltreatment, child welfare, and human services research share their insights and experiences at the forefront of this critical research area and how it is shaping understanding of identification, intervention, and policy affecting children and families.

Health care in the twenty-first century requires intensive use of technology in order to acquire and analyze data and manage and disseminate information. No area is more data intensive than the neurointensive care unit. Despite the massive amount of data, however, providers often lack interpretable and actionable information. This book reviews the concepts underlying the emerging field of neurocritical care informatics, with a focus on integrated data acquisition, linear and nonlinear processing, and innovative visualization in the ICU.

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection.

This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students.

A project based course to give you a glance of some good practices and common challenges while using Power BI

This volume focuses on innovative approaches and recent developments in clustering, analysis of data and models, and applications: The first part of the book covers a broad range of innovations in the area of clustering, from algorithmic innovations for graph clustering to new visualization and evaluation techniques.

The maturing of the field of data mining has brought about an increased level of mathematical sophistication. Such disciplines like topology, combinatorics, partially ordered sets and their associated algebraic structures (lattices and Boolean algebras), and metric spaces are increasingly applied in data mining research. This book presents these mathematical foundations of data mining integrated with applications to provide the reader with a comprehensive reference.