Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring.
Causal Inference in Pharmaceutical Statistics introduces the basic concepts and fundamental methods of causal inference relevant to pharmaceutical statistics.
This book presents the reader with comprehensive insight into various kinds of mathematical modeling and numerical computation for problems arising in several branches of engineering, such as mechanical engineering, computer science engineering, electrical engineering, electronics and communication engineering, and civil engineering.
Preeminent Experts Update a Well-Respected BookTaking into account the regulatory and scientific developments that have occurred since the second edition, Design and Analysis of Bioavailability and Bioequivalence Studies, Third Edition provides a complete presentation of the latest progress of activities and results in bioavailability and bioequiva
Managing Cooperation in Supply Network Structures and Small- or Medium-sized Enterprises outlines different approaches to the analysis of the organisation of small- or medium-sized enterprises (SMEs).
This book introduces the Learning-Augmented Network Optimization (LANO) paradigm, which interconnects network optimization with the emerging AI theory and algorithms and has been receiving a growing attention in network research.
This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability.
This book contains 43 papers form among the 55 papers presented at the Sixth International Conference on Fibonacci Numbers and Their Applications which was held at Washington State University, Pullman, Washington, from July 18-22, 1994.
Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology.
In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data.
This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients.
The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data.
This text shows how to use multivariate analysis to extract useful information from multivariate data and understand the structure of random phenomena.
Psychological Statistics: The Basics walks the reader through the core logic of statistical inference and provides a solid grounding in the techniques necessary to understand modern statistical methods in the psychological and behavioral sciences.
Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments.
This book explains the misuses and abuses of Null Hypothesis Significance Tests, which are reconsidered in light of Jeffreys' Bayesian concept of the role of statistical inference, in experimental investigations.
When a doctor tells you there's a one percent chance that an operation will result in your death, or a scientist claims that his theory is probably true, what exactly does that mean?
Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area.
Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening.
A complete guide to cutting-edge techniques and best practices for applying covariance analysis methods The Second Edition of Analysis of Covariance and Alternatives sheds new light on its topic, offering in-depth discussions of underlying assumptions, comprehensive interpretations of results, and comparisons of distinct approaches.
Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses.
Introduction to Regression Methods for Public Health Using R teaches regression methods for continuous, binary, ordinal, and time-to-event outcomes using R as a tool.
Proposing the concept of real-world data circulation (RWDC), this book presents various practical and industry-related studies in human, mechanical, and social data domains.
This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.
Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research.
A highly accessible alternative approach to basic statistics Praise for the First Edition: "e;Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see .
Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well.
Fourier Transforms of Distributions and Their Inverses: A Collection of Tables is a collection of tables on the integrals of Fourier transforms of distributions and their inverses involving the class of functions which are nonnegative and integrable over the interval.
This book primarily aims to discuss emerging topics in statistical methods and to booster research, education, and training to advance statistical modeling on interval-censored survival data.
