Engaging Political Philosophy introduces readers to the central problems of political philosophy. Presuming no prior work in the area, the book explores the fundamental philosophical questions regarding freedom, authority, justice, and democracy. More than a survey of the central figures and texts, Engaging Political Philosophy takes readers on a philosophical exploration of the core of the field, directly examining the arguments and concepts that drive the contemporary debates. Thus the fundamental issues of political philosophy are encountered first-hand, rather than through intermediary summaries of the major texts and theories. As a result, readers are introduced to political philosophy by doing philosophy. Written in a conversational style, Engaging Political Philosophy is accessible to students and general readers. Instructors can use it in the classroom as a stand-alone textbook, a complement to a standard collection of historical readings, or as a primer to be studied in preparation for contemporary readings.
Written specifically for those with no prior programming experience and minimal quantitative training, this accessible text walks behavioral science students and researchers through the process of programming using MATLAB. The book explores examples, terms, and programming needs relevant to those in the behavioral sciences and helps readers perform virtually any computational function in solving their research problems. Principles are illustrated with usable code. Each chapter opens with a list of objectives followed by new commands required to accomplish those goals. These objectives also serve as a reference to help readers easily relocate a section of interest. Sample code and output and chapter problems demonstrate how to write a program and explore a model so readers can see the results obtained using different equations and values. A web site provides solutions to selected problems and the book’s program code output and examples so readers can manipulate them as needed. The outputs on the website have color, motion, and sound. Highlights of the new edition include: •Updated to reflect changes in the most recent version of MATLAB, including special tricks and new functions. •More information on debugging and common errors and more basic problems in the rudiments of MATLAB to help novice users get up and running more quickly. •A new chapter on Psychtoolbox, a suite of programs specifically geared to behavioral science research. •A new chapter on Graphical User Interfaces (GUIs) for user-friendly communication. •Increased emphasis on pre-allocation of memory, recursion, handles, and matrix algebra operators. The book opens with an overview of what is to come and tips on how to write clear programs followed by pointers for interacting with MATLAB, including its commands and how to read error messages. The matrices chapter reviews how to store and access data. Chapter 4 examines how to carry out calculations followed by a review of how to perform various actions depending on the conditions. The chapter on input and output demonstrates how to design programs to create dialogs with users (e.g., participants in studies) and read and write data to and from external files. Chapter 7 reviews the data types available in MATLAB. Readers learn how to write a program as a stand-alone module in Chapter 8. In Chapters 9 and 10 readers learn how to create line and bar graphs or reshape images. Readers learn how to create animations and sounds in Chapter 11. The book concludes with tips on how to use MATLAB with applications such as GUIs and Psychtoolbox. Intended as a primary text for Matlab courses for advanced undergraduate and/or graduate students in experimental and cognitive psychology and/or neuroscience as well as a supplementary text for labs in data (statistical) analysis, research methods, and computational modeling (programming), the book also appeals to individual researchers in these disciplines who wish to get up and running in MATLAB.
How Behavioral Scientists and Others Can Learn From Mistakes for Better, Happier Programming
Author: David A. Rosenbaum
MATLAB Blues is an accessible, comprehensive introduction to the MATLAB computer programming language—a powerful and increasingly popular tool for students and researchers. Rosenbaum identifies many of the common mistakes and pitfalls associated with using MATLAB, and shows users how they can learn from these mistakes to be better, happier programmers. Each chapter systematically addresses one of the basic principles of the programming language, like matrices, calculations, contingencies, plotting, input-output, and graphics, and then identifies areas that are problematic, as well as potential errors that can occur. This not only provides the reader with the fundamental "scales and chords" that a MATLAB programmer needs to know, but also with a series of examples and explanations of how to avoid and remedy common mistakes. Accompanied by an array of sample code that can be used and manipulated in conjunction with the textbook, this book is a practical, insightful introduction to MATLAB which provides motivation and encouragement to those with little or no background in programming as well as to those with more advanced concerns. It is an invaluable resource for researchers and students undertaking courses in research methods, statistics, and programming.
Knowing Hands analyzes the cognitive psychology of manual control. This book will appeal to general readers interested in an accessible overview of the psychology and neuroscience underlying motor control. It will also serve as a supplemental text in a wide range of courses, including cognition, perception, occupational therapy, and robotics.
Motor Control is a complex process that involves the brain, muscles, limbs, and often external objects. It underlies motion, balance, stability, coordination, and our interaction with others and technology. This book is a comprehensive introduction to motor control, covering a complex topic in an approachable way encompassing the psychological, physiological, and computational approaches to motor control. Human Motor Control, 2e cuts across all movement related disciplines: physical education, dance, physical therapy, robotics, etc. This second edition incorporates advances to the field, and integrates throughout the book how research harkens back to four critical questions: how do we select our actions of the many actions possible? How are these behaviors sequenced for appropriate order and timing between them? How does perception integrate with motor control? And how are perceptual–motor skills acquired? As before, the book retains its signature organization around activity systems. These activity systems include walking, looking, reaching, drawing and writing, keyboarding, speaking and singing, and smiling. Chapters here exemplify rather than encompass all the behaviors related to them. Hence smiling discusses physical and neural control of the face used in other expressions besides smiling, as well as the origins of emotional expression, and the importance of emotion expression in social interaction. These chapters on activity systems are preceded by chapters on basics, with an introduction and information on the physiological and psychological foundations of movement. The last section discusses integration of movements, individual differences, theories of motor control, and the contributions of both genetics and technology to motor control. Special features of the second edition: Organization by major activity systems New: brain imaging, social action, embodied cognition, advances in genetics and technology Detailed treatment of motor neuroscience Further Readings section added to each chapter * Retains unique organization of first edition: Part 1 on Preliminaries, Part 2 on Activity Systems, Part 3 on Principles and Prospects * Emphasizes exciting advances in the field and promising new directions * Well-illustrated with entertaining figures
MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience
Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB® toolbox for the collection, visualization, and evaluation of experimental and real-life data Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® presents a practical approach to the task that biological scientists face when analyzing data. The primary focus is on the application of mathematical models and scientific computing methods to provide insight into the behavior of biological systems. The author draws upon his experience in academia, industry, and government–sponsored research as well as his expertise in MATLAB to produce a suite of computer programs with applications in epidemiology, machine learning, and biostatistics. These models are derived from real–world data and concerns. Among the topics included are the spread of infectious disease (HIV/AIDS) through a population, statistical pattern recognition methods to determine the presence of disease in a diagnostic sample, and the fundamentals of hypothesis testing. In addition, the author uses his professional experiences to present unique case studies whose analyses provide detailed insights into biological systems and the problems inherent in their examination. The book contains a well-developed and tested set of MATLAB functions that act as a general toolbox for practitioners of quantitative biology and biostatistics. This combination of MATLAB functions and practical tips amplifies the book’s technical merit and value to industry professionals. Through numerous examples and sample code blocks, the book provides readers with illustrations of MATLAB programming. Moreover, the associated toolbox permits readers to engage in the process of data analysis without needing to delve deeply into the mathematical theory. This gives an accessible view of the material for readers with varied backgrounds. As a result, the book provides a streamlined framework for the development of mathematical models, algorithms, and the corresponding computer code. In addition, the book features: Real–world computational procedures that can be readily applied to similar problems without the need for keen mathematical acumen Clear delineation of topics to accelerate access to data analysis Access to a book companion website containing the MATLAB toolbox created for this book, as well as a Solutions Manual with solutions to selected exercises Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® is an excellent textbook for students in mathematics, biostatistics, the life and social sciences, and quantitative, computational, and mathematical biology. This book is also an ideal reference for industrial scientists, biostatisticians, product development scientists, and practitioners who use mathematical models of biological systems in biomedical research, medical device development, and pharmaceutical submissions.
Cancer deaths per capita have decreased in recent years, but the improvement is attributed to prevention, not treatment. The difficulty in treating cancer may be due to its 'complexity', in the mathematical physics sense of the word. Tumors evolve and spread in response to internal and external factors that involve feedback mechanisms and nonlinear behavior. Investigations of the nonlinear interactions among cells, and between cells and their environment, are crucial for developing a sufficiently detailed understanding of the system's emergent phenomenology to be able to control the behavior. In the case of cancer, controlling the system's behavior will mean the ability to treat and cure the disease. Physicists have been studying various complex, nonlinear systems for many years using a variety of techniques. These investigations have provided insights that allow physicists to make unique contributions towards the treatment of cancer.This interdisciplinary book presents recent advancements in physicists' research on cancer. The work presented in this volume uses a variety of physical, biochemical, mathematical, theoretical, and computational techniques to gain a deeper molecular and cellular understanding of the horrific disease that is cancer.
Since the publication of the bestselling first edition, many advances have been made in exploratory data analysis (EDA). Covering innovative approaches for dimensionality reduction, clustering, and visualization, Exploratory Data Analysis with MATLAB®, Second Edition uses numerous examples and applications to show how the methods are used in practice. New to the Second Edition Discussions of nonnegative matrix factorization, linear discriminant analysis, curvilinear component analysis, independent component analysis, and smoothing splines An expanded set of methods for estimating the intrinsic dimensionality of a data set Several clustering methods, including probabilistic latent semantic analysis and spectral-based clustering Additional visualization methods, such as a rangefinder boxplot, scatterplots with marginal histograms, biplots, and a new method called Andrews’ images Instructions on a free MATLAB GUI toolbox for EDA Like its predecessor, this edition continues to focus on using EDA methods, rather than theoretical aspects. The MATLAB codes for the examples, EDA toolboxes, data sets, and color versions of all figures are available for download at http://pi-sigma.info
With Applications in the Social, Behavioral, and Health Sciences
Author: Linda M. Collins
Publisher: John Wiley & Sons
A modern, comprehensive treatment of latent class and latenttransition analysis for categorical data On a daily basis, researchers in the social, behavioral, andhealth sciences collect information and fit statistical models tothe gathered empirical data with the goal of making significantadvances in these fields. In many cases, it can be useful toidentify latent, or unobserved, subgroups in a population, whereindividuals' subgroup membership is inferred from their responseson a set of observed variables. Latent Class and LatentTransition Analysis provides a comprehensive and unifiedintroduction to this topic through one-of-a-kind, step-by-steppresentations and coverage of theoretical, technical, and practicalissues in categorical latent variable modeling for bothcross-sectional and longitudinal data. The book begins with an introduction to latent class and latenttransition analysis for categorical data. Subsequent chapters delveinto more in-depth material, featuring: A complete treatment of longitudinal latent class models Focused coverage of the conceptual underpinnings ofinterpretation and evaluationof a latent class solution Use of parameter restrictions and detection of identificationproblems Advanced topics such as multi-group analysis and the modelingand interpretation of interactions between covariates The authors present the topic in a style that is accessible yetrigorous. Each method is presented with both a theoreticalbackground and the practical information that is useful for anydata analyst. Empirical examples showcase the real-worldapplications of the discussed concepts and models, and each chapterconcludes with a "Points to Remember" section that contains a briefsummary of key ideas. All of the analyses in the book are performedusing Proc LCA and Proc LTA, the authors' own software packagesthat can be run within the SAS® environment. A related Website houses information on these freely available programs and thebook's data sets, encouraging readers to reproduce the analyses andalso try their own variations. Latent Class and Latent Transition Analysis is anexcellent book for courses on categorical data analysis and latentvariable models at the upper-undergraduate and graduate levels. Itis also a valuable resource for researchers and practitioners inthe social, behavioral, and health sciences who conduct latentclass and latent transition analysis in their everyday work.
Statistical Methods for Experiments, Quasi-Experiments, and Single-Case Studies
Author: Bradley Huitema
Publisher: John Wiley & Sons
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. The book has been extensively revised and updated to feature an in-depth review of prerequisites and the latest developments in the field. The author begins with a discussion of essential topics relating to experimental design and analysis, including analysis of variance, multiple regression, effect size measures and newly developed methods of communicating statistical results. Subsequent chapters feature newly added methods for the analysis of experiments with ordered treatments, including two parametric and nonparametric monotone analyses as well as approaches based on the robust general linear model and reversed ordinal logistic regression. Four groundbreaking chapters on single-case designs introduce powerful new analyses for simple and complex single-case experiments. This Second Edition also features coverage of advanced methods including: Simple and multiple analysis of covariance using both the Fisher approach and the general linear model approach Methods to manage assumption departures, including heterogeneous slopes, nonlinear functions, dichotomous dependent variables, and covariates affected by treatments Power analysis and the application of covariance analysis to randomized-block designs, two-factor designs, pre- and post-test designs, and multiple dependent variable designs Measurement error correction and propensity score methods developed for quasi-experiments, observational studies, and uncontrolled clinical trials Thoroughly updated to reflect the growing nature of the field, Analysis of Covariance and Alternatives is a suitable book for behavioral and medical scineces courses on design of experiments and regression and the upper-undergraduate and graduate levels. It also serves as an authoritative reference work for researchers and academics in the fields of medicine, clinical trials, epidemiology, public health, sociology, and engineering.
Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.
A reference devoted to the discussion of analysis of variance (ANOVA) techniques. It presents ANOVA as a research design, a collection of statistical models, an analysis model, and an arithmetic summary of data. Discussion focuses primarily on univariate data, but multivariate generalizations are to
Although its roots can be traced to the 19th century, progress in the study of nonlinear dynamical systems has taken off in the last 30 years. While pertinent source material exists, it is strewn about the literature in mathematics, physics, biology, economics, and psychology at varying levels of accessibility. A compendium research methods reflect
This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond “frequentist” concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called “hypothesis testing”) problems most frequently encountered in real-world applications.
The matrix laboratory interactive computing environment—MATLAB—has brought creativity to research in diverse disciplines, particularly in designing and programming experiments. More commonly used in mathematics and the sciences, it also lends itself to a variety of applications across the field of psychology. For the novice looking to use it in experimental psychology research, though, becoming familiar with MATLAB can be a daunting task. MATLAB for Psychologists expertly guides readers through the component steps, skills, and operations of the software, with plentiful graphics and examples to match the reader’s comfort level. Using an extended illustration, this concise volume explains the program’s usefulness at any point in an experiment, without the limits imposed by other types of software. And the authors demonstrate the responsiveness of MATLAB to the individual’s research needs, whether the task is programming experiments, creating sensory stimuli, running simulations, or calculating statistics for data analysis. Key features of the coverage: Thinking in a matrix way. Handling and plotting data. Guidelines for improved programming, sound, and imaging. Statistical analysis and signal detection theory indexes. The Graphical User Interface. The Psychophysics Toolbox. MATLAB for Psychologists serves a wide audience of advanced undergraduate and graduate level psychology students, professors, and researchers as well as lab technicians involved in programming psychology experiments.
Assuming no previous statistics education, this practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examples using real data, and includes a CD-ROM with software tools and data sets used in the examples and exercises. Readers learn which software tools to apply and also gain insights into the comparative capabilities of the primary software packages.
A one-of-a-kind presentation of the major achievements in statistical profile monitoring methods Statistical profile monitoring is an area of statistical quality control that is growing in significance for researchers and practitioners, specifically because of its range of applicability across various service and manufacturing settings. Comprised of contributions from renowned academicians and practitioners in the field, Statistical Analysis of Profile Monitoring presents the latest state-of-the-art research on the use of control charts to monitor process and product quality profiles. The book presents comprehensive coverage of profile monitoring definitions, techniques, models, and application examples, particularly in various areas of engineering and statistics. The book begins with an introduction to the concept of profile monitoring and its applications in practice. Subsequent chapters explore the fundamental concepts, methods, and issues related to statistical profile monitoring, with topics of coverage including: Simple and multiple linear profiles Binary response profiles Parametric and nonparametric nonlinear profiles Multivariate linear profiles monitoring Statistical process control for geometric specifications Correlation and autocorrelation in profiles Nonparametric profile monitoring Throughout the book, more than two dozen real-world case studies highlight the discussed topics along with innovative examples and applications of profile monitoring. Statistical Analysis of Profile Monitoring is an excellent book for courses on statistical quality control at the graduate level. It also serves as a valuable reference for quality engineers, researchers and anyone who works in monitoring and improving statistical processes.
The study of macroeconomics can seem a daunting project. The field is complex and sometimes poorly defined and there are a variety of competing approaches. It is easy for the senior bachelor and starting master student to get lost in the forest of macroeconomics and the mathematics it uses extensively. Foundations of Modern Macroeconomics is a guide book for the interested and ambitious student. Non-partisan in its approach, it deals with all the major topics, summarising the important approaches and providing the reader with a coherent angle on all aspects of macroeconomic thought. Each chapter deals with a separate area of macroeconomics, and each contains a summary section of key points and a further reading list. Using nothing more than undergraduate mathematical skills, it takes the student from basic IS-LM style macro models to the state of the art literature on Dynamic Stochastic General Equilibrium, explaining the mathematical tricks used where they are first introduced. Fully updated and substantially revised, this third edition of Foundations of Modern Macroeconomics now includes brand new chapters covering highly topical subjects such as dynamic programming, competitive risk sharing equilibria and the New Keynesian DSGE approach.