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Dash (Breyer Stablemates)
by J. Elizabeth MillsWhen Jenny discovers barrel racing, she cannot wait to give it a try. Luckily, Jenny's dad has the perfect horse, Dash. Dash is very fast, but Jenny must learn to control him around all the tight turns in the barrel racing course.
DAT 2017-2018 Strategies, Practice & Review with 2 Practice Tests: Online + Book
by KaplanWith Kaplan's DAT 2017-2018 Strategies, Practice & Review, you will gain an advantage by earning a higher Dental Admissions Test score - guaranteed or your money back. This book has all of the content and strategies you need to get the DAT results you want, including: * 2 full-length, online practice tests * 600+ practice questions * A guide to the current DAT Blueprint so you know exactly what to expect on Test Day * Kaplan's proven strategies for Test Day success * Comprehensive review of all of the content covered on the DAT: Biology, General Chemistry, Organic Chemistry, Perceptual Ability, Reading Comprehension, and Quantitative Reasoning * 12-page, tear-out, full-color study sheets for quick review on the go * Practice questions for every subject with answers and explanations Kaplan also offers a wide variety of additional DAT preparation options including online programs, books and software, classroom courses, and one-on-one tutoring. For more information about live events, courses, and other materials, visit KaplanDAT.com.
DAT Prep Plus 2019-2020: 2 Practice Tests + Proven Strategies + Online (Kaplan Test Prep)
by Kaplan Test PrepKaplan's DAT Prep Plus 2019-2020 provides the test-taking strategies, realistic practice, and expert guidance you need to score higher on the Dental Admissions Test. Our comprehensive updated subject review reflects recent changes to the blueprint of the exam, question types, and test interface. You'll get two full-length practice DATs and expert tips to help you face Test Day with confidence.The Best ReviewTwo updated full-length, online practice exams for test-like practiceStudy planning guidanceMore than 600 practice questions for every subject, with detailed answers and explanationsFull-color study sheets for high-yield reviewA guide to the current DAT Blueprint so you know exactly what to expect on Test DayComprehensive review of all of the content covered on the DATExpert GuidanceOur books and practice questions are written by veteran teachers who know students—every explanation is written to help you learnKaplan's experts ensure our practice questions and study materials are true to the testWe invented test prep—Kaplan (www.kaptest.com) has been helping students for 80 years, and our proven strategies have helped legions of students achieve their dreamsThe previous edition of this book was titled DAT 2017-2018 Strategies, Practice & Review.
DAT Prep Plus 2023-2024: 2 Practice Tests + Proven Strategies + Online (Kaplan Test Prep)
by Kaplan Test PrepKaplan's DAT Prep Plus 2023–2024 provides the test-taking strategies, realistic practice, and expert guidance you need to score higher on the Dental Admissions Test. Our comprehensive subject review reflects recent changes to the blueprint of the exam, question types, and test interface. You'll get two full-length practice DATs and expert tips to help you face Test Day with confidence.We're so confident that DAT Prep Plus offers all the knowledge you need to excel at the DAT that we guarantee it: after studying with our online resources and book, you'll score higher on the DAT—or you'll get your money back.The Best ReviewTwo updated full-length, online practice exams for test-like practiceStudy-planning guidanceMore than 600 practice questions for every subject, with detailed answers and explanations12-page full-color study sheets for high-yield review on the goA guide to the current DAT Blueprint so you know exactly what to expect on Test DayComprehensive review of all of the content covered on the DATExpert GuidanceOur books and practice questions are written by veteran teachers who know students—every explanation is written to help you learn.Kaplan's experts ensure our practice questions and study materials are true to the test.We invented test prep—Kaplan (www.kaptest.com) has been helping students for 80 years, and our proven strategies have helped legions of students achieve their dreams
Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
by Charles M. Judd Gary H. McClelland Carey S. RyanData Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and behavioral sciences. It covers all of the statistical models normally used in such analyses, such as multiple regression and analysis of variance, but it does so in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Data Analysis also describes how the model comparison approach and uniform framework can be applied to models that include product predictors (i.e., interactions and nonlinear effects) and to observations that are nonindependent. Indeed, the analysis of nonindependent observations is treated in some detail, including models of nonindependent data with continuously varying predictors as well as standard repeated measures analysis of variance. This approach also provides an integrated introduction to multilevel or hierarchical linear models and logistic regression. Finally, Data Analysis provides guidance for the treatment of outliers and other problematic aspects of data analysis. It is intended for advanced undergraduate and graduate level courses in data analysis and offers an integrated approach that is very accessible and easy to teach. Highlights of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with multiple random factors; updated examples; an enhanced website with PowerPoint presentations and other tools that demonstrate the concepts in the book; exercises for each chapter that highlight research findings from the literature; data sets, R code, and SAS output for all analyses; additional examples and problem sets; and test questions.
Data Analysis: A Model Comparison Approach, Second Edition
by Gary H. Mcclelland Carey S. Ryan Charles M. JuddThis completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. The authors show how all analysis of variance and multiple regression can be accomplished within this framework. The model-comparison approach provides several benefits: It strengthens the intuitive understanding of the material thereby increasing the ability to successfully analyze data in the future It provides more control in the analysis of data so that readers can apply the techniques to a broader spectrum of questions It reduces the number of statistical techniques that must be memorized It teaches readers how to become data analysts instead of statisticians. The book opens with an overview of data analysis. All the necessary concepts for statistical inference used throughout the book are introduced in Chapters 2 through 4. The remainder of the book builds on these models. Chapters 5 - 7 focus on regression analysis, followed by analysis of variance (ANOVA), mediational analyses, non-independent or correlated errors, including multilevel modeling, and outliers and error violations. The book is appreciated by all for its detailed treatment of ANOVA, multiple regression, nonindependent observations, interactive and nonlinear models of data, and its guidance for treating outliers and other problematic aspects of data analysis. Intended for advanced undergraduate or graduate courses on data analysis, statistics, and/or quantitative methods taught in psychology, education, or other behavioral and social science departments, this book also appeals to researchers who analyze data. A protected website featuring additional examples and problems with data sets, lecture notes, PowerPoint presentations, and class-tested exam questions is available to adopters. This material uses SAS but can easily be adapted to other programs. A working knowledge of basic algebra and any multiple regression program is assumed.
Data Analysis for Continuous School Improvement
by Victoria L. BernhardtThis book is a call to action. It is about inspiring schools and school districts to commit to continuous school improvement by providing a framework that will result in improving teaching for every teacher and learning for every student through the comprehensive use of data. A culmination of over 30 years of doing the hard work in schools and districts both nationally and internationally, Data Analysis for Continuous School Improvement shares new, evidence-based learnings about how to analyze, report, communicate, and use multiple measures of data. The updated edition provides a wealth of tools, protocols, timelines, examples, and strategies that will help schools and districts become genuine learning organizations. Data Analysis for Continuous School Improvement provides a new definition of school improvement, away from a singular focus on compliance, toward a true commitment to excellence.
Data Analysis Using SAS
by Dr Chao-Ying Joanne PengData Analysis Using SAS offers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market. It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems. Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student study at www.sagepub.com/pengstudy comes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book. Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.
Data Analytics and Adaptive Learning: Research Perspectives
by Patsy D. Moskal, Charles D. Dziuban, and Anthony G. PiccianoData Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.
Data Analytics Approaches in Educational Games and Gamification Systems (Smart Computing and Intelligence)
by Ahmed Tlili Maiga ChangGame-based learning environments and learning analytics are attracting increasing attention from researchers and educators, since they both can enhance learning outcomes. This book focuses on the application of data analytics approaches and research on human behaviour analysis in game-based learning environments, namely educational games and gamification systems, to provide smart learning. Specifically, it discusses the purposes, advantages and limitations of applying such approaches in these environments. Additionally, the various smart game-based learning environments presented help readers integrate learning analytics in their educational games and gamification systems to, for instance, assess and model students (e.g. their computational thinking) or enhance the learning process for better outcomes. Moreover, the book presents general guidelines on various aspects, such as collecting data for analysis, game-based learning environment design, system architecture and applied algorithms, which facilitate incorporating learning analytics into educational games and gamification systems.After a general introduction to help readers become familiar with the subject area, the individual chapters each discuss a different aim of applying data analytics approaches in educational games and gamification systems. Lastly, the conclusion provides a summary and presents general guidelines and frameworks to consider when designing smart game-based learning environments with learning analytics.
Data, Architecture and the Experience of Place
by Anastasia KarandinouThe notion of data is increasingly encountered in spatial, creative and cultural studies. Big data and artificial intelligence are significantly influencing a number of disciplines. Processes, methods and vocabularies from sciences, architecture, arts are borrowed, discussed and tweaked, and new cross-disciplinary fields emerge. More and more, artists and designers are drawing on hard data to interpret the world and to create meaningful, sensuous environments. Architects are using neurophysiological data to improve their understanding of people’s experiences in built spaces. Different disciplines collaborate with scientists to visualise data in different and creative ways, revealing new connections, interpretations and readings. This often demonstrates a genuine desire to comprehend human behaviour and experience and to – possibly – inform design processes accordingly. At the same time, this opens up questions as to why this desire and curiosity is emerging now, how it relates to recent technological advances and how it converses with the cultural, philosophical and methodological context of the disciplines with which it engages. Questions are also raised as to how the use of data and data-informed methods may serve, support, promote and/or challenge political agendas. Data, Architecture and the Experience of Place provides an overview of new approaches on this significant subject and is ideal for students and researchers in digital architecture, architectural theory, design, digital media, sensory studies and related fields.
Data Baby: My Life in a Psychological Experiment
by Susannah BreslinA Belletrist Book Pick for December 2023Lab Girl meets Brain on Fire in this provocative and poignant memoir delving into a woman's formative experiences as a veritable "lab rat" in a lifelong psychological study, and her pursuit to reclaim autonomy and her identity as a adult. What if your parents turn you into a human lab rat when you&’re a child? Will that change the story of your life? Will that change who you are? When Susannah Breslin is a toddler, her parents enroll her in an exclusive laboratory preschool at the University of California, Berkeley, where she becomes one of over a hundred children who are research subjects in an unprecedented thirty-year study of personality development that predicts who she and her cohort will grow up to be. Decades later, trapped in what she feels is an abusive marriage and battling breast cancer, she starts to wonder how growing up under a microscope shaped her identity and life choices. Already a successful journalist, she makes her own curious history the subject of her next investigation. From experiment rooms with one-way mirrors, to children&’s puzzles with no solutions, to condemned basement laboratories, her life-changing journey uncovers the long-buried secrets hidden behind the renowned study. The question at the gnarled heart of her quest: Did the study know her better than she knew herself? At once bravely honest and sharply witty, Data Baby is a compelling and provocative account of a woman&’s quest to find her true self, and an unblinking exploration of why we turn out as we do. Few people in all of history have been studied from such a young age and for as long as this author, but the message of her book is universal. In an era when so many of us are looking to technology to tell us who to be, it&’s up to us to discover who we actually are.
Data Base Manager: Passbooks Study Guide (Career Examination Series)
by National Learning CorporationThe Data Base Manager Passbook® prepares you for your test by allowing you to take practice exams in the subjects you need to study. It provides hundreds of questions and answers in the areas that will likely be covered on your upcoming exam, including but not limited to: programming techniques and concepts, including the use of pseudo language; project Management; principles and practices of data base administration; principles of databases for microcomputers; and more.
Data-based Decision Making in Education: Challenges and Opportunities (Studies in Educational Leadership #17)
by Mei Kuin Lai Lorna Earl Kim SchildkampIn a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students' assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are 'best practice' studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.
Data Center Virtualization Certification: Everything you need to achieve 2V0-622 certification – with exam tips and exercises
by Andrea Mauro Paolo ValsecchiDeploy and configure vSphere infrastructure and learn to effectively create and administer vSphere virtual machinesKey FeaturesImplement advanced network virtualization techniquesConfigure and administer vSphere high availabilityEnhance your data center virtualization skills with practice questions and mock testsBook DescriptionThis exam guide enables you to install, configure, and manage the vSphere 6.5 infrastructure in all its components: vCenter Server, ESXi hosts, and virtual machines, while helping you to prepare for the industry standard certification.This data center book will assist you in automating administration tasks and enhancing your environment’s capabilities. You will begin with an introduction to all aspects related to security, networking, and storage in vSphere 6.5. Next, you will learn about resource management and understand how to back up and restore the vSphere 6.5 infrastructure. As you advance, you will also cover troubleshooting, deployment, availability, and virtual machine management. This is followed by two mock tests that will test your knowledge and challenge your understanding of all the topics included in the exam.By the end of this book, you will not only have learned about virtualization and its techniques, but you’ll also be prepared to pass the VCP6.5-DCV (2V0-622) exam.What you will learnDeploy and configure vSphere infrastructureCreate and administer vSphere virtual machinesOptimize, secure, and troubleshoot all vSphere componentsImplement vSphere HA on a vSAN clusterUnderstand how to back up and restore your vSphere 6.5 infrastructureTest your understanding of key concepts required through sample questionsWho this book is forIf you are interested in achieving Data Center Virtualization certification, this is the book is for you. You will also benefit from this book if you are a system administrator or network engineer. Some prior knowledge of virtualization can assist you in understanding key concepts covered in the book.
The Data Coach's Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry
by Nancy Love Katherine E. Stiles Susan Mundry Kathryn DiRannaUse data as an effective tool for school change and improvement! This resource helps data team facilitators move schools away from unproductive data practices and toward examining data for systematic and continuous improvement in instruction and learning. The book, which includes a CD-ROM with slides and reproducibles, illustrates how the authors' model has proven successful in: Narrowing achievement gaps in all content areas and grade levels Achieving strong, continuous gains in local and state assessments in mathematics, science, and reading Initiating powerful conversations about race/ethnicity, class, educational status, gender, and language differences Developing a vision for a high-performing, data-informed school culture
The Data Coach's Guide to Improving Learning for All Students: Unleashing the Power of Collaborative Inquiry
by Nancy Love Katherine E. Stiles Susan Mundry Kathryn DiRannaUse data as an effective tool for school change and improvement! This resource helps data team facilitators move schools away from unproductive data practices and toward examining data for systematic and continuous improvement in instruction and learning. The book, which includes a CD-ROM with slides and reproducibles, illustrates how the authors' model has proven successful in: Narrowing achievement gaps in all content areas and grade levels Achieving strong, continuous gains in local and state assessments in mathematics, science, and reading Initiating powerful conversations about race/ethnicity, class, educational status, gender, and language differences Developing a vision for a high-performing, data-informed school culture
Data Collection: Planning for and Collecting All Types of Data
by Cathy A. Stawarski Patricia Pulliam PhillipsData Collection Data Collection is the second of six books in the Measurement and Evaluation Series from Pfeiffer. The proven ROI Methodology--developed by the ROI Institute--provides a practical system for evaluation planning, data collection, data analysis, and reporting. All six books in the series offer the latest tools, most current research, and practical advice for measuring ROI in a variety of settings. Data Collection offers an effective process for collecting data that is essential to the implementation of the ROI Methodology. The authors outline the techniques, processes, and critical issues involved in successful data collection. The book examines the various methods of data collection, including questionnaires, interviews, focus groups, observation, action plans, performance contracts, and monitoring records. Written for evaluators, facilitators, analysts, designers, coordinators, and managers, Data Collection is a valuable guide for collecting data that are adequate in quantity and quality to produce a complete and credible analysis.
Data Control Assistant: Passbooks Study Guide (Career Examination Series)
by National Learning CorporationThe Data Control Assistant Passbook® prepares you for your test by allowing you to take practice exams in the subjects you need to study. It provides hundreds of questions and answers in the areas that will likely be covered on your upcoming exam, including but not limited to: Coding/Decoding information; Logical reasoning using flow charts; Office record keeping; Understanding and interpreting a manual; and more.
Data Conversion: Calculating the Monetary Benefits
by Patricia Pulliam Phillips Holly BurkettThis book tackles the third major challenge and the second most difficult step in the ROI methodology: converting data to monetary values. When a particular project or program is connected to a business measure, the next logical question is: what is the monetary value of that impact? For ROI analysis, it is at this critical point where the monetary benefits are developed to compare to the costs of the program to calculate the ROI. Includes: the importance of converting data to monetary value; preliminary issues; standard values: the standard values: where to find them; using internal experts, using external databases; linking with other measures; using estimates; when to abandon conversion efforts and leave data as intangible, analyzing the intangibles; and reporting the intangibles.
Data Culture and the Organisation of Teachers’ Work: An Institutional Ethnography
by Nerida SpinaData Culture and the Organisation of Teachers’ Work provides an in-depth look at how the political and media scrutiny of teachers, pupils and schools now organises teaching and learning. Spina also examines how educational data is used in schools, and where it fails to take account of the everyday experiences of school leaders, teachers and students. Drawing on primary research, and discussing practice in relation to the National Assessment Programme: Literacy and Numeracy (NAPLAN), this book discusses the strengths and weaknesses of a data-driven approach, the restrictions this can impose and how to navigate them as a teacher. Ideal for scholars and postgraduate students of education, this book provides a comprehensive institutional, ethnographic look into the daily lived experiences of teachers, and the effects of standardised testing.
Data Cultures in Higher Education: Emergent Practices and the Challenge Ahead (Higher Education Dynamics #59)
by Juliana E. Raffaghelli Albert SangràThis collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and “formae mentis” to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with data. Notably, the book spots data practices within the two most relevant sides of academics’ professional practice, namely, research and teaching. Hence, the collection seeks to reflect on faculty’s professional learning about data infrastructures and practices.The book draws on a range of studies covering the higher education response to the several facets of data in society, from data surveillance and the algorithmic control of human behaviour to empowerment through the use of open data. The research reported ranges from literature overviews to multi-case and in-depth case studies illustrating institutional and educational responses to different problems connected to data. The ultimate intention is to provide conceptual bases and practical examples relating to universities’ faculty development policies to overcome data practices and discourses' fragmentation and contradictions: in a nutshell, to build “fair data cultures” in higher education.
Data Curious
by Carl Allchin Sarah NabelsiData has been a missing part of most academic curriculums for a long time, and we're all being affected. During challenging times, creating a data-informed culture can help you pivot quickly or prevent expensive missteps. Developing a data curious organization will take advantage of the burgeoning data resources available as a result of increasing digitalization.With this book, author Carl Allchin shows today's business professionals how to become data empowered. These tech-savvy business professionals will learn data literacy fundamentals—from understanding the possibilities to asking the right questions. You'll discover how to make the right technology choices and avoid pitfalls that could put your career and company at risk.Discover what an agile, empowered, data-driven organization should look likeExamine how to use data in new ways to help your business come to lifeLearn key terms and concepts around data management and analyticsUnderstand the differences between spreadsheet analysis and a data analytics pipelineGet advice for working with data scientists and explore ways to mitigate the IT department's concerns
Data, Data, Everywhere: Bringing All the Data Together for Continuous School Improvement
by Victoria L. Bernhardt<p>The latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. <p>Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.</p>
Data, Data Everywhere: Bringing All the Data Together for Continuous School Improvement
by Victoria L. BernhardtThe latest book from best-selling author Victoria L. Bernhardt is an easy-to-read primer that describes what it takes to achieve student learning growth at every grade level, in every subject area, and with every student group. In this new edition, readers will learn how to use data to inform their continuous school improvement as they develop an appreciation of the various types of data, uses for data, and how data are involved in the process. This accessible, updated edition provides a wealth of straightforward and accessible strategies that will allow educators to become comfortable with the many uses of data in increasing student improvement. Data, Data Everywhere, 2nd edition, provides a framework and summary of the continuous school improvement framework. It is a perfect resource for teachers, administrators, support staff, and students of leadership to guide comprehensive school improvement that will make a difference for all students.