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A Guide to Mathematics Coaching: Processes for Increasing Student Achievement
by Don S. Balka Ted H. Hull Ruth Harbin MilesDiscover how effective coaching relationships add up to improved mathematics teaching and learning! Based on principles established by NCTM and NCSM, this resource outlines a coaching process for engaging math teachers and fostering productive collaborations that lead to better teaching practice and increased student achievement. Focusing on the role of the math coach in transforming mathematics classrooms and ensuring equity, the chapters help coaches: Collaborate with teachers to align and implement curriculum Build trust and rapport with hesitant or resistant teachers Develop collegial partnerships for planning, analyzing, and reflecting on instruction Support and sustain individual and institutional change
A Guide to Mathematics Leadership: Sequencing Instructional Change
by Don S. Balka Ted H. Hull Ruth Harbin MilesWritten by three noted mathematics educators, this volume presents a process-based approach to building a high-quality mathematics program based on five NCTM principles and four NCSM leadership principles.
A Guide to Monte Carlo Simulations in Statistical Physics
by David Landau Kurt BinderDealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. The 5th edition contains extensive new material describing numerous powerful algorithms and methods that represent recent developments in the field. New topics such as active matter and machine learning are also introduced. Throughout, there are many applications, examples, recipes, case studies, and exercises to help the reader fully comprehend the material. This book is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
A Guide to Monte Carlo Simulations in Statistical Physics
by David P. Landau Kurt Binder David P. Landau Kurt BinderDealing with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics and statistical mechanics, this book provides an introduction to computer simulations in physics. This fourth edition contains extensive new material describing numerous powerful algorithms not covered in previous editions, in some cases representing new developments that have only recently appeared. Older methodologies whose impact was previously unclear or unappreciated are also introduced, in addition to many small revisions that bring the text and cited literature up to date. This edition also introduces the use of petascale computing facilities in the Monte Carlo arena. Throughout the book there are many applications, examples, recipes, case studies, and exercises to help the reader understand the material. It is ideal for graduate students and researchers, both in academia and industry, who want to learn techniques that have become a third tool of physical science, complementing experiment and analytical theory.
A Guide to Monte Carlo Simulations in Statistical Physics
by David P. Landau Kurt BinderThis new and updated edition deals with all aspects of Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. After briefly recalling essential background in statistical mechanics and probability theory, it gives a succinct overview of simple sampling methods. The concepts behind the simulation algorithms are explained comprehensively, as are the techniques for efficient evaluation of system configurations generated by simulation. It contains many applications, examples, and exercises to help the reader and provides many new references to more specialized literature. This edition includes a brief overview of other methods of computer simulation and an outlook for the use of Monte Carlo simulations in disciplines beyond physics. This is an excellent guide for graduate students and researchers who use computer simulations in their research. It can be used as a textbook for graduate courses on computer simulations in physics and related disciplines.
A Guide to NIP Theories
by Pierre SimonThe study of NIP theories has received much attention from model theorists in the last decade, fuelled by applications to o-minimal structures and valued fields. This book, the first to be written on NIP theories, is an introduction to the subject that will appeal to anyone interested in model theory: graduate students and researchers in the field, as well as those in nearby areas such as combinatorics and algebraic geometry. Without dwelling on any one particular topic, it covers all of the basic notions and gives the reader the tools needed to pursue research in this area. An effort has been made in each chapter to give a concise and elegant path to the main results and to stress the most useful ideas. Particular emphasis is put on honest definitions, handling of indiscernible sequences and measures. The relevant material from other fields of mathematics is made accessible to the logician.
A Guide to Numerical Modelling in Systems Biology (Texts in Computational Science and Engineering #12)
by Peter Deuflhard Susanna RöblitzThis book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.
A Guide to Outcome Modeling In Radiotherapy and Oncology: Listening to the Data (Series in Medical Physics and Biomedical Engineering)
by Issam El NaqaThis book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven approaches. This book is primarily intended to act as a tutorial for newcomers to the field of outcome modeling, as it includes in-depth how-to recipes on modeling artistry while providing sufficient instruction on how such models can approximate the physical and biological realities of clinical treatment. The book will also be of value to seasoned practitioners as a reference on the varying aspects of outcome modeling and their current applications. Features: Covers top-down approaches applying statistical, machine learning, and big data analytics and bottom-up approaches using first principles and multi-scale techniques, including numerical simulations based on Monte Carlo and automata techniques Provides an overview of the available software tools and resources for outcome model development and evaluation, and includes hands-on detailed examples throughout Presents a diverse selection of the common applications of outcome modeling in a wide variety of areas: treatment planning in radiotherapy, chemotherapy and immunotherapy, utility-based and biomarker applications, particle therapy modeling, oncological surgery, and the design of adaptive and SMART clinical trials
A Guide to Penrose Tilings
by Francesco D'AndreaThis book provides an elementary introduction, complete with detailed proofs, to the celebrated tilings of the plane discovered by Sir Roger Penrose in the '70s. Quasi-periodic tilings of the plane, of which Penrose tilings are the most famous example, started as recreational mathematics and soon attracted the interest of scientists for their possible application in the description of quasi-crystals. The purpose of this survey, illustrated with more than 200 figures, is to introduce the curious reader to this beautiful topic and be a reference for some proofs that are not easy to find in the literature. The volume covers many aspects of Penrose tilings, including the study, from the point of view of Connes' Noncommutative Geometry, of the space parameterizing these tilings.
A Guide to Publishing for Academics: Inside the Publish or Perish Phenomenon
by Jay LiebowitzMost academics still wrestle with the "publish or perish" phenomenon. Based on Dr. Liebowitz's 25 years serving as the editor-in-chief of a leading international journal, along with insights from some of the most knowledgeable journal editors, this book shares key lessons learned to help new professors, doctoral students, and practitioner-scholars
A Guide to Qualitative Field Research
by Carol A. BaileyThoroughly revised, the Second Edition of A Guide to Qualitative Field Research provides novice researchers with comprehensive and accessible instructions for conducting qualitative field research. Using rich examples from classic ethnographies to help bring abstract principles alive, author Carol A. Bailey thoroughly explains the entire research process from selecting a topic to writing the final manuscript, and all of the steps in between!
A Guide to R for Social and Behavioral Science Statistics
by Brian Joseph Gillespie Dr. William E. Wagner Kathleen Charli HibbertA Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R, geared toward social and behavioral science students. Instructors Brian Gillespie, Kathleen Hibbert, and William E. Wagner, III, have combined a review of introductory statistics with an introduction to R to teach readers two of the most valuable skills for research and in the workplace. Designed for readers with no knowledge of statistics or R, A Guide to R for Social and Behavioral Science Statistics follows the most common progression of statistics, starting with basic descriptive statistics, and continuing up through inferential statistics and regression. This text provides step-by-step instructions for working with R, starting with downloading and installing R and RStudio®, featuring code and output so readers can follow along with each step. Readers can apply their knowledge with examples and exercises featuring data from the General Social Survey in each chapter. Tips on R show users how to avoid common pitfalls in R and most efficiently use the RStudio interface. With frequent reminders of statistical concepts to accompany instructions and tips in R, this text helps readers master R for statistics in the social and behavioral sciences.
A Guide to R for Social and Behavioral Science Statistics
by Brian Joseph Gillespie Dr. William E. Wagner Kathleen Charli HibbertA Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R, geared toward social and behavioral science students. Instructors Brian Gillespie, Kathleen Hibbert, and William E. Wagner, III, have combined a review of introductory statistics with an introduction to R to teach readers two of the most valuable skills for research and in the workplace. Designed for readers with no knowledge of statistics or R, A Guide to R for Social and Behavioral Science Statistics follows the most common progression of statistics, starting with basic descriptive statistics, and continuing up through inferential statistics and regression. This text provides step-by-step instructions for working with R, starting with downloading and installing R and RStudio®, featuring code and output so readers can follow along with each step. Readers can apply their knowledge with examples and exercises featuring data from the General Social Survey in each chapter. Tips on R show users how to avoid common pitfalls in R and most efficiently use the RStudio interface. With frequent reminders of statistical concepts to accompany instructions and tips in R, this text helps readers master R for statistics in the social and behavioral sciences.
A Guide to Research Methodology: An Overview of Research Problems, Tasks and Methods
by Shyama Prasad MukherjeeResearch Methodology is meant to provide a broad guideline to facilitate and steer the whole of a research activity in any discipline. With the ambit and amount of research increasing by the day, the need for Research Methodology is being widely appreciated. Against this backdrop, we notice the dearth of well-written books on the subject. A Guide to Research Methodology attempts a balance between the generic approach to research in any domain and the wide array of research methods which are to be used in carrying out different tasks in any research. Discussions on these research methods appropriate in various disciplines have focused on the research tasks, keeping in mind the fact that a single such task like a comparison among alternatives may involve several methods from seemingly distinct areas. Unique features of this volume, as will be evident to a discerning reader, include: A detailed discussion on problem areas for research in several domains An illustrative and ampliated list of research problems drawn from different disciplines which can be pursued by interested research workers A comprehensive delineation of Research Design supported by illustrations An elaborate engagement with models with a note on model uncertainty Focus on recent and emerging models, methods and techniques A novel treatment of data analysis where the nature of data and the objective(s) of analysis justify drawing upon a variety of techniques for analysis This book will serve the purpose of a pre-PhD or a Master-level course-work for students of any discipline with a basic knowledge of quantitative analysis. In fact, anyone aspiring to take up meaningful research work will find the content useful and interesting.
A Guide to Robust Statistical Methods
by Rand R. WilcoxRobust statistical methods are now being used in a wide range of disciplines. The appeal of these methods is that they are designed to perform about as well as classic techniques when standard assumptions are true—but they continue to perform well in situations where classic methods perform poorly. This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data. The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
A Guide to Sample Size for Animal-based Studies
by Penny S. ReynoldsA Guide to Sample Size for Animal-based Studies Understand a foundational area of experimental design with this innovative reference Animal-based research is an essential part of basic and preclinical research, but poses a unique set of experimental design challenges. The most important of these are the 3Rs − Replacement, Reduction and Refinement − the principles comprising the ethical framework for humane animal-based studies. However, many researchers have difficulty navigating the design trade-offs necessary to simultaneously minimize animal use, and produce scientific information that is both rigorous and reliable. A Guide to Sample Size for Animal-based Studies meets this need with a thorough, accessible reference work to the subject. This book provides a straightforward systematic approach to “rightsizing” animal-based experiments, with sample size estimates based on the fundamentals of statistical thinking: structured research questions, variation control and appropriate design of experiments. The result is a much-needed guide to planning animal-based experiments to ensure scientifically valid and reliable results. This book offers: Step-by-step guidance in diverse methods for approximating and refining sample size Detailed treatment of research topics specific to animal-based research, including pilot, feasibility and proof-of-concept studies Sample size approximation methods for different types of data − binary, continuous, ordinal, time to event − and different study types − description, comparison, nested designs, reference interval construction and dose-response studies Numerous worked examples, using real data from published papers, together with SAS and R code A Guide to Sample Size for Animal-based Studies is a must-have reference for preclinical and veterinary researchers, as well as ethical oversight committees and policymakers.
A Guide to Signals and Systems in Continuous Time
by Stéphane LafortuneThis textbook is a concise yet precise supplement to traditional books on Signals and Systems, focusing exclusively on the continuous-time case. Students can use this guide to review material, reinforce their understanding, and see how all the parts connect together in a uniform treatment focused on mathematical clarity. Readers learn the “what”, “why” and “how” about the ubiquitous Fourier and Laplace transforms encountered in the study of linear time-invariant systems in engineering: what are these transforms, why do we need them, and how do we use them? Readers will come away with an understanding of the gradual progression from time-domain analysis to frequency-domain and s-domain techniques for continuous-time linear time-invariant systems. This book reflects the author’s experience in teaching this material for over 25 years in sophomore- and junior-level required engineering courses and is ideal for undergraduate classes in electrical engineering.
A Guide to Spectral Theory: Applications and Exercises (Birkhäuser Advanced Texts Basler Lehrbücher)
by Christophe Cheverry Nicolas RaymondThis textbook provides a graduate-level introduction to the spectral theory of linear operators on Banach and Hilbert spaces, guiding readers through key components of spectral theory and its applications in quantum physics. Based on their extensive teaching experience, the authors present topics in a progressive manner so that each chapter builds on the ones preceding. Researchers and students alike will also appreciate the exploration of more advanced applications and research perspectives presented near the end of the book.Beginning with a brief introduction to the relationship between spectral theory and quantum physics, the authors go on to explore unbounded operators, analyzing closed, adjoint, and self-adjoint operators. Next, the spectrum of a closed operator is defined and the fundamental properties of Fredholm operators are introduced. The authors then develop the Grushin method to execute the spectral analysis of compact operators. The chapters that follow are devoted to examining Hille-Yoshida and Stone theorems, the spectral analysis of self-adjoint operators, and trace-class and Hilbert-Schmidt operators. The final chapter opens the discussion to several selected applications. Throughout this textbook, detailed proofs are given, and the statements are illustrated by a number of well-chosen examples. At the end, an appendix about foundational functional analysis theorems is provided to help the uninitiated reader.A Guide to Spectral Theory: Applications and Exercises is intended for graduate students taking an introductory course in spectral theory or operator theory. A background in linear functional analysis and partial differential equations is assumed; basic knowledge of bounded linear operators is useful but not required. PhD students and researchers will also find this volume to be of interest, particularly the research directions provided in later chapters.
A Guide to the Classification Theorem for Compact Surfaces (Geometry and Computing #9)
by Dianna Xu Jean GallierThis welcome boon for students of algebraic topology cuts a much-needed central path between other texts whose treatment of the classification theorem for compact surfaces is either too formalized and complex for those without detailed background knowledge, or too informal to afford students a comprehensive insight into the subject. Its dedicated, student-centred approach details a near-complete proof of this theorem, widely admired for its efficacy and formal beauty. The authors present the technical tools needed to deploy the method effectively as well as demonstrating their use in a clearly structured, worked example. Ideal for students whose mastery of algebraic topology may be a work-in-progress, the text introduces key notions such as fundamental groups, homology groups, and the Euler-Poincaré characteristic. These prerequisites are the subject of detailed appendices that enable focused, discrete learning where it is required, without interrupting the carefully planned structure of the core exposition. Gently guiding readers through the principles, theory, and applications of the classification theorem, the authors aim to foster genuine confidence in its use and in so doing encourage readers to move on to a deeper exploration of the versatile and valuable techniques available in algebraic topology.
A Handbook of Public Speaking for Scientists and Engineers
by Peter KennyA Handbook of Public Speaking for Scientists and Engineers helps scientists and engineers improve their skills at speaking in public in the course of their professional activities. The book shows how best to prepare papers for presentation at a technical conference and how to put cases to committee meetings. Not only does the book deal with specific events, but it also provides the techniques of more effective speaking, whether presenting papers, answering questions, or speaking "off-the-cuff." The book is written in a highly entertaining manner and should put all complacent lecturers on their guard.
A Handbook of Statistical Analyses Using S-PLUS
by Brian S. EverittSince the first edition of this book was published, S-PLUS has evolved markedly with new methods of analysis, new graphical procedures, and a convenient graphical user interface (GUI). Today, S-PLUS is the statistical software of choice for many applied researchers in disciplines ranging from finance to medicine. Combining the command line languag
A Handbook of Statistical Analyses using R
by Brian S. Everitt Torsten HothornLike the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive partitioning to cluster analysis.New to the Third Edition
A Handbook of Statistical Analyses using SAS
by Brian S. Everitt Geoff DerUpdated 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 of analysis. The authors cover inference, analysis of variance, regression, generalized linear mo
A Handbook of Statistical Graphics Using SAS ODS
by Brian Everitt Geoff DerEasily Use SAS to Produce Your GraphicsDiagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full gr
A Handbook of Test Construction: Introduction to Psychometric Design (Psychology Revivals)
by Paul KlinePsychological tests provide reliable and objective standards by which individuals can be evaluated in education and employment. Therefore accurate judgements must depend on the reliability and quality of the tests themselves. Originally published in 1986, this handbook by an internationally acknowledged expert provided an introductory and comprehensive treatment of the business of constructing good tests. Paul Kline shows how to construct a test and then to check that it is working well. Covering most kinds of tests, including computer presented tests of the time, Rasch scaling and tailored testing, this title offers: a clear introduction to this complex field; a glossary of specialist terms; an explanation of the objective of reliability; step-by-step guidance through the statistical procedures; a description of the techniques used in constructing and standardizing tests; guidelines with examples for writing the test items; computer programs for many of the techniques. Although the computer testing will inevitably have moved on, students on courses in occupational, educational and clinical psychology, as well as in psychological testing itself, would still find this a valuable source of information, guidance and clear explanation.