Statistical Inference

The risks posed by climate change and its effect on climate extremes are an increasingly pressing societal problem. This book provides an accessible overview of the statistical analysis methods which can be used to investigate climate extremes and analyse potential risk. The statistical analysis methods are illustrated with case studies on extremes in the three major climate variables: temperature, precipitation, and wind speed. The book also provides datasets and access to appropriate analysis software, allowing the reader to replicate the case study calculations. Providing the necessary tools to analyse climate risk, this book is invaluable for students and researchers working in the climate sciences, as well as risk analysts interested in climate extremes.

Good scientific research depends on critical thinking at least as much as factual knowledge; psychology is no exception to this rule. And yet, despite the importance of critical thinking, psychology students are rarely taught how to think critically about the theories, methods, and concepts they must use. This book shows students and researchers how to think critically about key topics such as experimental research, statistical inference, case studies, logical fallacies, and ethical judgments. Using updated research findings and new insights, this volume provides a comprehensive overview of what critical thinking is and how to teach it in psychology. Written by leading experts in critical thinking in psychology, each chapter contains useful pedagogical features, such as critical-thinking questions, brief summaries, and definitions of key terms. It also supplies descriptions of each chapter author's critical-thinking experience, which evidences how critical thinking has made a differenc

Good scientific research depends on critical thinking at least as much as factual knowledge; psychology is no exception to this rule. And yet, despite the importance of critical thinking, psychology students are rarely taught how to think critically about the theories, methods, and concepts they must use. This book shows students and researchers how to think critically about key topics such as experimental research, statistical inference, case studies, logical fallacies, and ethical judgments. Using updated research findings and new insights, this volume provides a comprehensive overview of what critical thinking is and how to teach it in psychology. Written by leading experts in critical thinking in psychology, each chapter contains useful pedagogical features, such as critical-thinking questions, brief summaries, and definitions of key terms. It also supplies descriptions of each chapter author's critical-thinking experience, which evidences how critical thinking has made a differenc

The fourth edition of Statistical Concepts for the Behavioral Sciences emphasizes contemporary research problems to better illustrate the relevance of statistical analysis in scientific research. All statistical methods are introduced in the context of a realistic problem, many of which are from contemporary published research. These studies are fully referenced so students can easily access the original research. The uses of statistics are then developed and presented in a conceptually logical progression for increased comprehension by using the accompanying workbook and the problem sets. Several forms of practice problems are available to students and presented in a manner that assists students in mastering component pieces before integrating them together to tackle more complicated, real-world problems.

Although numerical approximation and statistical inference are traditionally covered as entirely separate subjects, they are intimately connected through the common purpose of making estimations with partial information. This book explores these connections from a game and decision theoretic perspective, showing how they constitute a pathway to developing simple and general methods for solving fundamental problems in both areas. It illustrates these interplays by addressing problems related to numerical homogenization, operator adapted wavelets, fast solvers, and Gaussian processes. This perspective reveals much of their essential anatomy and greatly facilitates advances in these areas, thereby appearing to establish a general principle for guiding the process of scientific discovery. This book is designed for graduate students, researchers, and engineers in mathematics, applied mathematics, and computer science, and particularly researchers interested in drawing on and developing this

The edition of Basics of Statistics and Statistical Application with Excel emphasizes concepts of statistics,statistical methods are carefully presented with a focus on understanding both the suitabil

Lab Manual for Psychological Research and Statistical Analysis serves as an additional resource for students and instructors in a research methods, statistics, or combined course where classroom and/o

Advanced statistical modeling and knowledge representation techniques for a newly emerging area of machine learning and probabilistic reasoning; includes introductory material, tutorials for different

1. Applied Linear Statistical Models contains 14 chapters on the Applied Linear Regression Models, plus an additional 16 chapters on single and multifactor ANOVA and Experimental Design. The standard

Lecturers teaching big mixed cohort intro statistics courses cite one of the more frequent challenges their students encounter involves choices over which statistical test to use. Students, even if th

Developed specifically for students in the behavioral and brain sciences, this is the only textbook that provides an accessible and practical overview of the range of human neuroimaging techniques. Methods covered include functional and structural magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, multimodal imaging, and various brain stimulation methods. Experimental design, image processing, and statistical inference are also addressed, with chapters for both basic and more advanced data analyses. Key concepts are illustrated through research studies on the relationship between brain and behavior, and practice questions are included throughout to test knowledge and aid self-study. Offering just the right amount of detail for understanding how major imaging techniques can be applied to answer neuroscientific questions, and the practical skills needed for future research, this is an essential text for advanced undergraduate and gra

Developed specifically for students in the behavioral and brain sciences, this is the only textbook that provides an accessible and practical overview of the range of human neuroimaging techniques. Methods covered include functional and structural magnetic resonance imaging, positron emission tomography, electroencephalography, magnetoencephalography, multimodal imaging, and various brain stimulation methods. Experimental design, image processing, and statistical inference are also addressed, with chapters for both basic and more advanced data analyses. Key concepts are illustrated through research studies on the relationship between brain and behavior, and practice questions are included throughout to test knowledge and aid self-study. Offering just the right amount of detail for understanding how major imaging techniques can be applied to answer neuroscientific questions, and the practical skills needed for future research, this is an essential text for advanced undergraduate and gra

Statistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of trying to meet the needs of students, researchers and operational practitioners. This updated edition not on

This book develops in detail the statistical foundations of nonequilibrium thermodynamics, based on the mathematical theory of Brownian motion. Author Bernard H. Lavenda demonstrates that thermodynami

This monograph constructs classical statistical mechanics as a deductive system, based on the equations of motion and the basic postulates of probability. The treatment consists chiefly of theorems an

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt

Statistical mechanics: the bane of many a physics student, and traditionally viewed as a long parade of ensembles, partition functions, and partial derivatives. But the subject needn't be arcane

You can't get anywhere in your statistics course without grasping statistical significance. it's often seen as difficult but is actually a straightforward concept everyone can - and should - understan

This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and exci

Proficiency with using Excel® is a key skill set students need when going on to graduate school in the behavioral sciences. Students struggle to understand core statistical concepts, and there is a ne

The Statistical Abstract of the United States is the best known statistical reference. As a comprehensive collection of statistics on the social, political, and economic conditions of the country, it

This authoritative text offers a complete overview on the statistical mechanics and electrodynamics of physical processes in dense plasma systems. The author emphasizes laboratory-based experiments an

This authoritative text offers a complete overview on the statistical mechanics and electrodynamics of physical processes in dense plasma systems. The author emphasizes laboratory-based experiments an

This book presents different data collection and representation techniques: elementary descriptive statistics, confirmatory statistics, multivariate approaches and statistical modeling. It exposes the

Statistical, Mapping and Digital Approaches in Healthcare addresses all health territories, starting from the analysis of geographical data (health data, population data, health data systems and envir

Statistical Methods for Overdispersed Count Data provides a review of the most recent methods and models for such data, including a description of R functions and packages that allow their implementat

An updated edition of a classic text on applying statistical analyses to the social sciences, with reviews, new chapters, an expanded set of post-hoc analyses, and information on computing in Excel an

This research monograph utilizes exact and Monte Carlo permutation statistical methods to generate probability values and measures of effect size for a variety of measures of association. Association

An open and dynamic software for statistical analysis, R has become increasingly popular among students and researchers alike for its powerful language and graphical abilities. This book inc

The Statistical Yearbook is an annual compilation of a wide range of international economic, social and environmental statistics on over 200 countries and areas, compiled from sources including UN age

Human Development Indices and Indicators: 2018 Statistical Update is being released to ensure consistency in reporting on key human development indices and statistics.

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, a

The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control – a practical guide in the mid-eighties. Then people

The business, commercial and public-sector world has changed dramatically since John Oakland wrote the first edition of Statistical Process Control – a practical guide in the mid-eighties. Then people

This book presents statistical downscaling techniques in a practical manner so that readers can easily adopt the techniques for hydrological applications and designs in response to climate change. It

Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

This book focuses on Erdélyi–Kober fractional calculus from a statistical perspective inspired by solar neutrino physics. Results of diffusion entropy analysis and standard deviation analysis of data

Presents a unified approach to parametric estimation, confidence intervals, hypothesis testing, and statistical modeling, which are uniquely based on the likelihood function This book addresses mathem

This book focuses on the spatial distribution of landslide hazards of the Darjeeling Himalayas. Knowledge driven methods and statistical techniques such as frequency ratio model (F

This book covers all aspects of statistical methods in detail with applications. It presents solutions to the needs of post-graduate medical students, doctors and basic medical scientists for statisti