General

Understand How to Analyze and Interpret Information in Ecological Point PatternsAlthough numerous statistical methods for analyzing spatial point patterns have been available for several decades, they haven't been extensively applied in an ecological...

This book introduces optimal control problems for large families of deterministic and stochastic systems with discrete or continuous time parameter. These families include most of the systems studied in many disciplines, including Economics, Engineering,...

An Introduction to the Rasch Model with Examples in R offers a clear, comprehensive introduction to the Rasch model along with practical examples in the free, open-source software R. It is accessible for readers without a background in psychometrics or...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781032242002Author Taylor H. LewisFormat PaperbackPage Count 340Imprint Taylor & Francis LtdPublisher Taylor & Francis LtdWeight(grams) 156g

Statisticians have met the need to test hundreds or thousands of genomics hypotheses simultaneously with novel empirical Bayes methods that combine advantages of traditional Bayesian and frequentist statistics. Techniques for estimating the local false...

This book presents modern nonparametric statistics from a practical point of view. This new edition includes custom R functions implementing nonparametric methods to explain how to compute them and make them more comprehensible. Relevant built-in...

A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing...

Randomization, Masking, and Allocation Concealment is indispensable for any trial researcher who wants to use state of the art randomization methods, and also wants to be able to describe these methods correctly. Far too often the subtle nuances...

Using Predictive Analytics to Improve Healthcare OutcomesWinner of the American Journal of Nursing (AJN) Informatics Book of the Year Award 2021! Discover a comprehensive overview, from established leaders in the field, of how to use predictive analytics...

Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of...

DESIGNING BIG DATA PLATFORMS Provides expert guidance and valuable insights on getting the most out of Big Data systemsAn array of tools are currently available for managing and processing data-some are ready-to-go solutions that can be immediately...

A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft(R) Office Excel(R) applications used to guide business decision making Featuring quantitative techniques essential for modeling modern business situations,...

This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis? How should it be taught? What...

Most texts on experimental design fall into one of two distinct categories. There are theoretical works with few applications and minimal discussion on design, and there are methods books with limited or no discussion of the underlying theory...

The Monte Carlo method is a numerical method of solving mathematical problems through random sampling. As a universal numerical technique, the method became possible only with the advent of computers, and its application continues to expand with each new...

Users of statistics in their professional lives and statistics students will welcome this concise, easy-to-use reference for basic statistics and probability. It contains all of the standardized statistical tables and formulas typically needed plus...

This work details the fundamentals of applied statistics and experimental design, presenting a unified approach to data handling that emphasizes the analysis of variance, regression analysis and the use of Statistical Analysis System computer programs...

Since publication of the first edition in 1992, the field of survey sampling has grown considerably. This new edition of Survey Sampling: Theory and Methods has been updated to include the latest research and the newest methods. The authors have...

In this book the authors have assembled the best techniques from a great variety of sources, establishing a benchmark for the field of statistical computing. ---Mathematics of Computation . The text is highly readable and well illustrated with examples...

Showcasing a discussion of the experimental process and a review of basic statistics, this volume provides methodologies to identify general data distribution, skewness, and outliers. It features a unique classification of the nonparametric analogs of...

A nonlinear Markov evolution is a dynamical system generated by a measure-valued ordinary differential equation with the specific feature of preserving positivity. This feature distinguishes it from general vector-valued differential equations and yields...

This second edition of Daniel W. Stroock's text is suitable for first-year graduate students with a good grasp of introductory, undergraduate probability theory and a sound grounding in analysis. It is intended to provide readers with an introduction to...

With meta-analysis methods playing a crucial role in health research in recent years, this important and clearly-written book provides a much-needed survey of the field. Meta-analysis provides a framework for combining the results of several clinical...

One in a series of books co-published with SAS, this book provides a user-friendly introduction to both the SAS system and elementary statistical procedures for researchers and students in the Social Sciences. This Second Edition, updated to cover...

Praise for the First Edition "This book ...is a significant addition to the literature on statistical practice ...should be of considerable interest to those interested in these topics."-International Journal of Forecasting Recent research has...

Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes - such as the distribution of pollution - vary. The techniques used in...

Introducing a novel approach to setting environmental pollution standards that allow for proper treatment of uncertainty and variation, this book surveys the forms of standards and proposes a new kind of "statistically verifiable ideal standard...

Spatio-Temporal Methods in Environmental Epidemiology with R, like its first Edition, explores the interface between environmental epidemiology and spatio-temporal modelling. It links recent developments in spatio-temporal theory with epidemiological...

Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse...

Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and...

Research data is expensive and precious, yet it is seldom fully utilized due to our ability of comprehension. Graphical display is desirable, if not absolutely necessary, for fully understanding large data sets with complex interconnectedness and...

Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions,...

Presents a novel approach to the statistical design of experiments, offering a simple way to specify and evaluate all possible designs without restrictions to classes of named designs. The work also presents a scientific design method from the...

Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity...

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of...

Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with...

Although the basic statistical theory behind modern genetics is not very difficult, most statistical genetics papers are not easy to read for beginners in the field, and formulae quickly become very tedious to fit a particular area of application. ...

Updated to reflect SAS 9.2, A Handbook of Statistical Analyses using SAS, Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS. Each chapter shows how to use SAS for a particular type...

With numerous real-world examples, Modelling and Quantitative Methods in Fisheries, Second Edition provides an introduction to the analytical methods used by fisheries' scientists and ecologists. By following the examples using Excel, readers see the...

Written to meet the needs of both students and applied researchers, Design of Experiments for Agriculture and the Natural Sciences, Second Edition serves as an introductory guide to experimental design and analysis. Like the popular original, this...