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Doing Quantitative Research in Education with IBM SPSS Statistics

This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics. Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.

Doing Research: A New Researcher’s Guide (Research in Mathematics Education)

This book is about scientific inquiry. Designed for early and mid-career researchers, it is a practical manual for conducting and communicating high-quality research in (mathematics) education. Based on the authors’ extensive experience as researchers, as mentors, and as members of the editorial team for the Journal for Research in Mathematics Education (JRME), this book directly speaks to researchers and their communities about each phase of the process for conceptualizing, conducting, and communicating high-quality research in (mathematics) education.In the late 2010s, both JRME and Educational Studies in Mathematics celebrated 50 years of publishing high-quality research in mathematics education. Many advances in the field have occurred since the establishment of these journals, and these anniversaries marked a milestone in research in mathematics education. Indeed, fifty years represents a small step for human history but a giant leap for mathematics education. The educational research community in general (and the mathematics education community in particular) has strongly advocated for original research, placing great emphasis on building knowledge and capacity in the field. Because it is an interdisciplinary field, mathematics education has integrated means and methods for scientific inquiry from multiple disciplines. Now that the field is gaining maturity, it is a good time to take a step back and systematically consider how mathematics education researchers can engage in significant, impactful scientific inquiry.

Doing Social Research and Publishing Results: A Guide To Non-native English Speakers

Doing Statistical Analysis: A Student’s Guide to Quantitative Research

Doing Statistical Analysis looks at three kinds of statistical research questions – descriptive, associational, and inferential – and shows students how to conduct statistical analyses and interpret the results. Keeping equations to a minimum, it uses a conversational style and relatable examples such as football, COVID-19, and tourism, to aid understanding. Each chapter contains practice exercises, and a section showing students how to reproduce the statistical results in the book using Stata and SPSS. Digital supplements consist of data sets in Stata, SPSS, and Excel, and a test bank for instructors. Its accessible approach means this is the ideal textbook for undergraduate students across the social and behavioral sciences needing to build their confidence with statistical analysis.

Doing Statistical Analysis: A Student’s Guide to Quantitative Research

Doing Statistical Analysis looks at three kinds of statistical research questions – descriptive, associational, and inferential – and shows students how to conduct statistical analyses and interpret the results. Keeping equations to a minimum, it uses a conversational style and relatable examples such as football, COVID-19, and tourism, to aid understanding. Each chapter contains practice exercises, and a section showing students how to reproduce the statistical results in the book using Stata and SPSS. Digital supplements consist of data sets in Stata, SPSS, and Excel, and a test bank for instructors. Its accessible approach means this is the ideal textbook for undergraduate students across the social and behavioral sciences needing to build their confidence with statistical analysis.

Doing Statistics with SPSS (PDF)

`This book is to be commended, particularly, for putting the tool of statistics into the familiar context of a research study. In so doing it emphasizes the neglected pre-analysis stages of a research study. Indeed the performing of a data analysis, this book reminds us, should be the mere icing on an already well cooked cake' - Psychology Learning amp; Teaching. Doing Statistics With SPSS is derived from the authors' many years of experience teaching undergraduates data handling using SPSS. It assumes no prior understanding beyond that of basic mathematical operations and is therefore suitable for anyone undertaking an introductory statistics course as part of a science based undergraduate programme. The text will: enable the reader to make informed choices about what statistical tests to employ; what assumptions are made in using a particular test; demonstrate how to execute the analysis using SPSS; and guide the reader in his//her interpretation of its output. Each chapter ends with an exercise and provides detailed instructions on how to run the analysis using SPSS release 10. Learning is further guided by pointing the reader to particular aspects of the SPSS output and by having the reader engage with specified items of information from the SPSS results. This text is more complete than the alternatives that usually fall into one of two camps. They either provide an explanation of the concepts but no instructions on how to execute the analysis with SPSS, or they are a manual which instructs the reader on how to drive the software but with minimal explanation of what it all means. This book offers the best elements of both in a style that is economical and accessible. Doing Statistics with SPSS will be essential reading for undergraduates in psychology and health-related disciplines, and likely to be of invaluable use to many other students in the social sciences taking a course in statistics.

Doing Transitions in the Life Course: Processes and Practices (Life Course Research and Social Policies #16)

This open access book provides a unique research perspective on life course transitions. Here, transitions are understood as social processes and practices. Leveraging the recent “practice turn” in the social sciences, the contributors analyze how life course transitions are “done.” This book introduces the concept of “doing transitions” and its implications for theories and methods. It presents fresh empirical research on “doing transitions” in different life phases (e.g., childhood, young adulthood, later life) and life domains (e.g., education, work, family, health, migration). It also emphasizes themes related to institutions and organizations, time and normativity, materialities (such as bodies, spaces, and artifacts), and the reproduction of social inequalities in education and welfare. In coupling this new perspective with empirical illustrations, this book is an indispensable resource for scholars from demography, sociology, psychology, social work and other scientific fields, as well as for students, counselors and practitioners, and policymakers.

Doing Worlds with Words: Formal Semantics without Formal Metaphysics (Synthese Library #253)

Doing Worlds with Words throws light on the problem of meaning as the meeting point of linguistics, logic and philosophy, and critically assesses the possibilities and limitations of elucidating the nature of meaning by means of formal logic, model theory and model-theoretical semantics. The main thrust of the book is to show that it is misguided to understand model theory metaphysically and so to try to base formal semantics on something like formal metaphysics; rather, the book states that model theory and similar tools of the analysis of language should be understood as capturing the semantically relevant, especially inferential, structure of language. From this vantage point, the reader gains a new light on many of the traditional concepts and problems of logic and philosophy of language, such as meaning, reference, truth and the nature of formal logic.

Dokumentation in der Mess- und Prüftechnik: Messen - Auswerten - Darstellen Protokolle - Berichte - Präsentationen

Dieser praxisorientierte Leitfaden vermittelt Grundlagen für Datenauswertung und Dokumentation in natur- und ingenieurwissenschaftlichen Studiengängen. Von Fehleranalyse über Datenvisualisierung bis zur elektronischen Dokumentation bietet das Buch präzise Einblicke in relevante Themen.

Domain Adaptation and Representation Transfer: 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings (Lecture Notes in Computer Science #13542)

This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022. DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.

Domain Adaptation and Representation Transfer: 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings (Lecture Notes in Computer Science #14293)

This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023. The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.

Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning: Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings (Lecture Notes in Computer Science #12444)

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic. For DART 2020, 12 full papers were accepted from 18 submissions. They deal with methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings by making them robust and consistent across different domains.For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases; where information privacy is a priority; where it is necessary to deliver strong guarantees on the amount and nature of private information that may be revealed by the model as a result of training; and where it's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task.

Domain Conditions and Social Rationality

This book primarily focuses on the domain conditions under which a number of important classes of binary social decision rules give rise to rational social preferences. One implication of the Arrow and Gibbard theorems is that every non-oligarchic social decision rule that satisfies the condition of independence of irrelevant alternatives, a requirement crucial for the unambiguity of social choices, and the weak Pareto criterion fails to generate quasi-transitive social preferences for some configurations of individual preferences. The problem is exemplified by the famous voting paradox associated with the majority rule. Thus, in the context of rules that do not give rise to transitive (quasi-transitive) social preferences for every configuration of individual preferences, an important problem is that of formulating Inada-type necessary and sufficient conditions for transitivity (quasi-transitivity). This book formulates conditions for transitivity and quasi-transitivity for several classes of social decision rules, including majority rules, non-minority rules, Pareto-inclusive non-minority rules, and social decision rules that are simple games. It also analyzes in detail the conditions for transitivity and quasi-transitivity under the method of the majority decision, and derives the maximally sufficient conditions for transitivity under the class of neutral and monotonic binary social decision rules and one of its subclasses. The book also presents characterizations of some of the classes of rules for which domain conditions have been derived. The material covered is relevant to anyone interested in studying the structure of voting rules, particularly those interested in social choice theory. Providing the necessary social choice theoretic concepts, definitions, propositions and theorems, the book is essentially self-contained. The treatment throughout is rigorous, and unlike most of the literature on domain conditions, care is taken regarding the number of individuals in the 'necessity' proofs. As such it is an invaluable resource for students of economics and political science, with takeaways for everyone – from first-year postgraduates to more advanced doctoral students and scholars.

Domain Decomposition Methods - Algorithms and Theory (Springer Series in Computational Mathematics #34)

This book offers a comprehensive presentation of some of the most successful and popular domain decomposition preconditioners for finite and spectral element approximations of partial differential equations. It places strong emphasis on both algorithmic and mathematical aspects. It covers in detail important methods such as FETI and balancing Neumann-Neumann methods and algorithms for spectral element methods.

Domain Decomposition Methods for the Numerical Solution of Partial Differential Equations (Lecture Notes in Computational Science and Engineering #61)

Domain decomposition methods are divide and conquer computational methods for the parallel solution of partial differential equations of elliptic or parabolic type. The methodology includes iterative algorithms, and techniques for non-matching grid discretizations and heterogeneous approximations. This book serves as a matrix oriented introduction to domain decomposition methodology. A wide range of topics are discussed include hybrid formulations, Schwarz, and many more.

Domain Decomposition Methods in Optimal Control of Partial Differential Equations (International Series of Numerical Mathematics #148)

While domain decomposition methods have a long history dating back well over one hundred years, it is only during the last decade that they have become a major tool in numerical analysis of partial differential equations. This monograph emphasizes domain decomposition methods in the context of so-called virtual optimal control problems and treats optimal control problems for partial differential equations and their decompositions using an all-at-once approach.

Domain Decomposition Methods in Science and Engineering (Lecture Notes in Computational Science and Engineering #40)

Domain decomposition is an active, interdisciplinary research area that is devoted to the development, analysis and implementation of coupling and decoupling strategies in mathematics, computational science, engineering and industry. A series of international conferences starting in 1987 set the stage for the presentation of many meanwhile classical results on substructuring, block iterative methods, parallel and distributed high performance computing etc. This volume contains a selection from the papers presented at the 15th International Domain Decomposition Conference held in Berlin, Germany, July 17-25, 2003 by the world's leading experts in the field. Its special focus has been on numerical analysis, computational issues,complex heterogeneous problems, industrial problems, and software development.

Domain Decomposition Methods in Science and Engineering XIX (Lecture Notes in Computational Science and Engineering #78)

These are the proceedings of the 19th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very large linear or nonlinear systems of algebraic equations that arise in various problems in mathematics, computational science, engineering and industry. They are designed for massively parallel computers and take the memory hierarchy of such systems into account. This is essential for approaching peak floating point performance. There is an increasingly well-developed theory which is having a direct impact on the development and improvement of these algorithms.

Domain Decomposition Methods in Science and Engineering XVI (Lecture Notes in Computational Science and Engineering #55)

Domain decomposition is an active research area concerned with the development, analysis, and implementation of coupling and decoupling strategies in mathematical and computational models of natural and engineered systems. The present volume sets forth new contributions in areas of numerical analysis, computer science, scientific and industrial applications, and software development.

Domain Decomposition Methods in Science and Engineering XVII (Lecture Notes in Computational Science and Engineering #60)

Domain decomposition is an active, interdisciplinary research field concerned with the development, analysis, and implementation of coupling and decoupling strategies in mathematical and computational models. This volume contains selected papers presented at the 17th International Conference on Domain Decomposition Methods in Science and Engineering. It presents the newest domain decomposition techniques and examines their use in the modeling and simulation of complex problems.

Domain Decomposition Methods in Science and Engineering XVIII (Lecture Notes in Computational Science and Engineering #70)

th This volume contains a selection of 41 refereed papers presented at the 18 International Conference of Domain Decomposition Methods hosted by the School of ComputerScience and Engineering(CSE) of the Hebrew Universityof Jerusalem, Israel, January 12–17, 2008. 1 Background of the Conference Series The International Conference on Domain Decomposition Methods has been held in twelve countries throughout Asia, Europe, the Middle East, and North America, beginning in Paris in 1987. Originally held annually, it is now spaced at roughly 18-month intervals. A complete list of past meetings appears below. The principal technical content of the conference has always been mathematical, but the principal motivation has been to make ef cient use of distributed memory computers for complex applications arising in science and engineering. The leading 15 such computers, at the “petascale” characterized by 10 oating point operations per second of processing power and as many Bytes of application-addressablem- ory, now marshal more than 200,000 independentprocessor cores, and systems with many millions of cores are expected soon. There is essentially no alternative to - main decomposition as a stratagem for parallelization at such scales. Contributions from mathematicians, computerscientists, engineers,and scientists are together n- essary in addressing the challenge of scale, and all are important to this conference.

Domain Decomposition Methods in Science and Engineering XX (Lecture Notes in Computational Science and Engineering #91)

These are the proceedings of the 20th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very large linearor nonlinear systems of algebraic equations that arise when various problems in continuum mechanics are discretized using finite elements. They are designed for massively parallel computers and take the memory hierarchy of such systems in mind. This is essential for approaching peak floating point performance. There is an increasingly well developed theory whichis having a direct impact on the development and improvements of these algorithms.​

Domain Decomposition Methods in Science and Engineering XXI (Lecture Notes in Computational Science and Engineering #98)

This volume contains a selection of papers presented at the 21st international conference on domain decomposition methods in science and engineering held in Rennes, France, June 25-29, 2012. Domain decomposition is an active and interdisciplinary research discipline, focusing on the development, analysis and implementation of numerical methods for massively parallel computers. Domain decomposition methods are among the most efficient solvers for large scale applications in science and engineering. They are based on a solid theoretical foundation and shown to be scalable for many important applications. Domain decomposition techniques can also naturally take into account multiscale phenomena. This book contains the most recent results in this important field of research, both mathematically and algorithmically and allows the reader to get an overview of this exciting branch of numerical analysis and scientific computing.

Domain Decomposition Methods in Science and Engineering XXII (Lecture Notes in Computational Science and Engineering #104)

These are the proceedings of the 22nd International Conference on Domain Decomposition Methods, which was held in Lugano, Switzerland. With 172 participants from over 24 countries, this conference continued a long-standing tradition of internationally oriented meetings on Domain Decomposition Methods. The book features a well-balanced mix of established and new topics, such as the manifold theory of Schwarz Methods, Isogeometric Analysis, Discontinuous Galerkin Methods, exploitation of modern HPC architectures and industrial applications. As the conference program reflects, the growing capabilities in terms of theory and available hardware allow increasingly complex non-linear and multi-physics simulations, confirming the tremendous potential and flexibility of the domain decomposition concept.

Domain Decomposition Methods in Science and Engineering XXIV (Lecture Notes in Computational Science and Engineering #125)

These are the proceedings of the 24th International Conference on Domain Decomposition Methods in Science and Engineering, which was held in Svalbard, Norway in February 2017. Domain decomposition methods are iterative methods for solving the often very large systems of equations that arise when engineering problems are discretized, frequently using finite elements or other modern techniques. These methods are specifically designed to make effective use of massively parallel, high-performance computing systems. The book presents both theoretical and computational advances in this domain, reflecting the state of art in 2017.