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Learning From Data

Author: Arthur Glenberg
Publisher: Routledge
ISBN: 1136676627
Size: 39.94 MB
Format: PDF
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Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to helpstudents better understand relevant data that affecttheir everyday lives. Numerous examples based on current research and events are featured throughout.To facilitate learning, authors Glenberg and Andrzejewski: Devote extra attention to explaining the more difficult concepts and the logic behind them Use repetition to enhance students’ memories with multiple examples, reintroductions of the major concepts, and a focus on these concepts in the problems Employ a six-step procedure for describing all statistical tests from the simplest to the most complex Provide end-of-chapter tables to summarize the hypothesis testing procedures introduced Emphasizes how to choose the best procedure in the examples, problems and endpapers Focus on power with a separate chapter and power analyses procedures in each chapter Provide detailed explanations of factorial designs, interactions, and ANOVA to help students understand the statistics used in professional journal articles. The third edition has a user-friendly approach: Designed to be used seamlessly with Excel, all of the in-text analyses are conducted in Excel, while the book’s CD contains files for conducting analyses in Excel, as well as text files that can be analyzed in SPSS, SAS, and Systat Two large, real data sets integrated throughout illustrate important concepts Many new end-of-chapter problems (definitions, computational, and reasoning) and many more on the companion CD Online Instructor’s Resources includes answers to all the exercises in the book and multiple-choice test questions with answers Boxed media reports illustrate key concepts and their relevance to realworld issues The inclusion of effect size in all discussions of power accurately reflects the contemporary issues of power, effect size, and significance. Learning From Data, Third Edition is intended as a text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.

Learning From Data

Author: Beth Ann Haines
Publisher: Psychology Press
ISBN: 9780805817850
Size: 64.58 MB
Format: PDF, Docs
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This manual supplements Learning from Data: An Introduction to Statistical Reasoning. The chapter organization of the manual corresponds to that of the textbook. Each chapter of the manual is in two parts. The first part contains answers to the end-of-chapter exercises in the textbook. The second part contains multiple-choice questions from which instructors can make up tests.

Learning From Data An Introduction To Statistical Reasoning

Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1467254088
Size: 70.66 MB
Format: PDF, Docs
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Facts101 is your complete guide to Learning from Data , An Introduction to Statistical Reasoning. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Designing Surveys

Author: Ron Czaja
Publisher: Pine Forge Press
ISBN: 9780761927464
Size: 29.93 MB
Format: PDF, ePub, Mobi
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The Second Edition of Designing Surveys: A Guide to Decisions and Procedures accounts for changes in telephone, Internet, and email surveying and provides a more comprehensive treatment on questionnaire testing. Despite changing technologies, however, the principles of scientific survey design remain unchanged, including the selection of the sample, the writing of questions to solicit an unbiased response, and the ethical treatment of human subjects. This new edition addresses these issues in the context of new and emerging technologies and their relationship to survey design and the social sciences. Designing Surveys provides an accurate account of how modern survey research is actually conducted, but with the needs and goals of a novice researcher in mind.

Introduction To Social Statistics

Author: Thomas Dietz
Publisher: John Wiley & Sons
ISBN: 1405169028
Size: 24.48 MB
Format: PDF, Mobi
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Introduction to Social Statistics is a basic statistics text with a focus on the use of models for thinking through statistical problems, an accessible and consistent structure with ongoing examples across chapters, and an emphasis on the tools most commonly used in contemporary research. Lively introductory textbook that uses three strategies to help students master statistics: use of models throughout; repetition with variation to underpin pedagogy; and emphasis on the tools most commonly used in contemporary research Demonstrates how more than one statistical method can be used to approach a research question Enhanced learning features include a walk–through of statistical concepts, applications, features, advanced topics boxes, and a What Have We Learned section at the end of each chapter Supported by a website containing instructor materials including chapter–by–chapter PowerPoint slides, answers to exercises, and an instructor guide Visit www.wiley.com/go/dietz for additional student and instructor resources.

Introduction To Statistical Reasoning

Author: Gary Smith
Publisher: McGraw-Hill College
ISBN: 9780070592766
Size: 53.86 MB
Format: PDF, ePub, Docs
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This text focuses on the analysis of data and the interpretation of results rather than the computational methods of statistics. Its examples are taken from a broad range of disciplines and screen shots from the more popular software packages are included to display data and graphics. Mathematical derivations are minimized, so encouraging the student to use a calculator or computer to perform the computations. Various technology options give the student a range of methods for performing the statistical computations. The section on uses and misuses of statistics shows how statistics are presented by graphs and charts.

Introduction To Statistical Relational Learning

Author: Lise Getoor
Publisher: MIT Press
ISBN: 0262072882
Size: 19.72 MB
Format: PDF
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Advanced statistical modeling and knowledge representation techniques for a newly emerging area of machine learning and probabilistic reasoning; includes introductory material, tutorials for different proposed approaches, and applications. Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases and programming languages to represent structure. In Introduction to Statistical Relational Learning, leading researchers in this emerging area of machine learning describe current formalisms, models, and algorithms that enable effective and robust reasoning about richly structured systems and data. The early chapters provide tutorials for material used in later chapters, offering introductions to representation, inference and learning in graphical models, and logic. The book then describes object-oriented approaches, including probabilistic relational models, relational Markov networks, and probabilistic entity-relationship models as well as logic-based formalisms including Bayesian logic programs, Markov logic, and stochastic logic programs. Later chapters discuss such topics as probabilistic models with unknown objects, relational dependency networks, reinforcement learning in relational domains, and information extraction. By presenting a variety of approaches, the book highlights commonalities and clarifies important differences among proposed approaches and, along the way, identifies important representational and algorithmic issues. Numerous applications are provided throughout.

Statistics Learning From Data

Author: Roxy Peck
Publisher: Cengage Learning
ISBN: 1337672157
Size: 76.53 MB
Format: PDF, ePub, Mobi
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STATISTICS: LEARNING FROM DATA, Second Edition, addresses common problems faced by learners of elementary statistics with an innovative approach. The authors have paid particular attention to areas learners often struggle with -- probability, hypothesis testing, and selecting an appropriate method of analysis. Probability coverage is based on current research on how students best learn the subject. A unique chapter that provides an informal introduction to the ideas of statistical inference helps students to develop a framework for choosing an appropriate method. Supported by learning objectives, real-data examples and exercises, and technology notes, this book helps learners to develop conceptual understanding, mechanical proficiency, and the ability to put knowledge into practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Developing Students Statistical Reasoning

Author: Joan Garfield
Publisher: Springer Science & Business Media
ISBN: 1402083831
Size: 57.17 MB
Format: PDF, ePub, Mobi
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Increased attention is being paid to the need for statistically educated citizens: statistics is now included in the K-12 mathematics curriculum, increasing numbers of students are taking courses in high school, and introductory statistics courses are required in college. However, increasing the amount of instruction is not sufficient to prepare statistically literate citizens. A major change is needed in how statistics is taught. To bring about this change, three dimensions of teacher knowledge need to be addressed: their knowledge of statistical content, their pedagogical knowledge, and their statistical-pedagogical knowledge, i.e., their specific knowledge about how to teach statistics. This book is written for mathematics and statistics educators and researchers. It summarizes the research and highlights the important concepts for teachers to emphasize, and shows the interrelationships among concepts. It makes specific suggestions regarding how to build classroom activities, integrate technological tools, and assess students’ learning. This is a unique book. While providing a wealth of examples through lessons and data sets, it is also the best attempt by members of our profession to integrate suggestions from research findings with statistics concepts and pedagogy. The book’s message about the importance of listening to research is loud and clear, as is its message about alternative ways of teaching statistics. This book will impact instructors, giving them pause to consider: "Is what I’m doing now really the best thing for my students? What could I do better?" J. Michael Shaughnessy, Professor, Dept of Mathematical Sciences, Portland State University, USA This is a much-needed text for linking research and practice in teaching statistics. The authors have provided a comprehensive overview of the current state-of-the-art in statistics education research. The insights they have gleaned from the literature should be tremendously helpful for those involved in teaching and researching introductory courses. Randall E. Groth, Assistant Professor of Mathematics Education, Salisbury University, USA

Reconceptualizing Early Mathematics Learning

Author: Lyn D. English
Publisher: Springer Science & Business Media
ISBN: 9400764405
Size: 31.86 MB
Format: PDF, Docs
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This book emanated primarily from concerns that the mathematical capabilities of young children continue to receive inadequate attention in both the research and instructional arenas. Research over many years has revealed that young children have sophisticated mathematical minds and a natural eagerness to engage in a range of mathematical activities. As the chapters in this book attest, current research is showing that young children are developing complex mathematical knowledge and abstract reasoning a good deal earlier than previously thought. A range of studies in prior to school and early school settings indicate that young learners do possess cognitive capacities which, with appropriately designed and implemented learning experiences, can enable forms of reasoning not typically seen in the early years. Although there is a large and coherent body of research on individual content domains such as counting and arithmetic, there have been remarkably few studies that have attempted to describe characteristics of structural development in young students’ mathematics. Collectively, the chapters highlight the importance of providing more exciting, relevant, and challenging 21st century mathematics learning for our young students. The chapters provide a broad scope in their topics and approaches to advancing young children’s mathematical learning. They incorporate studies that highlight the importance of pattern and structure across the curriculum, studies that target particular content such as statistics, early algebra, and beginning number, and studies that consider how technology and other tools can facilitate early mathematical development. Reconceptualising the professional learning of teachers in promoting young children’s mathematics, including a consideration of the role of play, is also addressed.