R Companion to Epidemiology: Study Design and Data Analysis is a companion volume to the classic textbook by Mark Woodward, Epidemiology: Study Design and Data Analysis, Third Edition.
R Companion to Epidemiology: Study Design and Data Analysis is a companion volume to the classic textbook by Mark Woodward, Epidemiology: Study Design and Data Analysis, Third Edition.
Quantitative Methods for Second Language Research introduces approaches to and techniques for quantitative data analysis in second language research, with a primary focus on second language learning and assessment research.
BIOCALCULUS: CALCULUS, PROBABILITY, AND STATISTICS FOR THE LIFE SCIENCES shows you how calculus relates to biology, illustrating the topics of calculus with [real-life?
Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data.
Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on optimization techniques used to solve problems with adaptive, dynamic, and stochastic features.
Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations.
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms.
Confidence Intervals for Proportions and Related Measures of Effect Size illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests.
Drawing on the authors' two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the fundamental background required for analyzing data and building models for many practical applications, such as consumer behavior modeling, risk and marketing analytics, and other areas.
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms.
Written by an experienced researcher and portfolio manager who coined the term "e;risk parity,"e; this book provides readers with a practical understanding of the risk parity investment approach.
Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management.
This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting.
This book introduces and discusses the most important aspects of clinical research methods and biostatistics for oncologists, pursuing a tailor-made and practical approach.
This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences.
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data.
Das vorliegende Buch soll einen ersten Eindruck von den Möglichkeiten des Programmsystems SPSS vermitteln und die ersten eigenen Anwendungen erleichtern.
