Fundamentals Of Statistical Reasoning In Education With Cd With Essentials Of Statistics Set
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Fundamentals Of Statistical Reasoning In Education With Cd With Essentials Of Statistics Set
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Author : Theodore Coladarci
language : en
Publisher:
Release Date : 2006-07-01
Fundamentals Of Statistical Reasoning In Education With Cd With Essentials Of Statistics Set written by Theodore Coladarci and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-01 with categories.
Developing Students Statistical Reasoning
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Author : Joan Garfield
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-08
Developing Students Statistical Reasoning written by Joan Garfield and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-08 with Education categories.
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 theliterature should be tremendously helpful for those involved in teaching and researching introductory courses. Randall E. Groth, Assistant Professor of Mathematics Education, Salisbury University, USA
Learning From Data
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Author : Arthur Glenberg
language : en
Publisher: Routledge
Release Date : 2007-08-09
Learning From Data written by Arthur Glenberg and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-09 with Education categories.
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 downloadable resources contain 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.
All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
The Challenge Of Developing Statistical Literacy Reasoning And Thinking
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Author : Dani Ben-Zvi
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-02-23
The Challenge Of Developing Statistical Literacy Reasoning And Thinking written by Dani Ben-Zvi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-23 with Mathematics categories.
Research in statistics education is an emerging field, with much of the work being published in diverse journals across many disciplines. Locating and synthesizing this research is often a challenging task, as is connecting the research literature to practical issues of teaching and assessing students. This book is unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels. Unlike other books on how to teach statistics, or educational materials to help students learn statistics, this book presents the research foundation on which teaching should be based. The chapters in this volume are written by the today's leading researchers in statistics education. This volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
Fundamentals Of Mathematical Statistics
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Author : S.C. Gupta
language : en
Publisher: Sultan Chand & Sons
Release Date : 2020-09-10
Fundamentals Of Mathematical Statistics written by S.C. Gupta and has been published by Sultan Chand & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Mathematics categories.
Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Knowledge updating is a never-ending process and so should be the revision of an effective textbook. The book originally written fifty years ago has, during the intervening period, been revised and reprinted several times. The authors have, however, been thinking, for the last few years that the book needed not only a thorough revision but rather a substantial rewriting. They now take great pleasure in presenting to the readers the twelfth, thoroughly revised and enlarged, Golden Jubilee edition of the book. The subject-matter in the entire book has been re-written in the light of numerous criticisms and suggestions received from the users of the earlier editions in India and abroad. The basis of this revision has been the emergence of new literature on the subject, the constructive feedback from students and teaching fraternity, as well as those changes that have been made in the syllabi and/or the pattern of examination papers of numerous universities. Some prominent additions are given below: 1. Variance of Degenerate Random Variable 2. Approximate Expression for Expectation and Variance 3. Lyapounov’s Inequality 4. Holder’s Inequality 5. Minkowski’s Inequality 6. Double Expectation Rule or Double-E Rule and many others
Fundamentals Of Statistical Inference
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Author : Norbert Hirschauer
language : en
Publisher: Springer Nature
Release Date : 2022-08-18
Fundamentals Of Statistical Inference written by Norbert Hirschauer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-18 with Mathematics categories.
This book provides a coherent description of foundational matters concerning statistical inference and shows how statistics can help us make inductive inferences about a broader context, based only on a limited dataset such as a random sample drawn from a larger population. By relating those basics to the methodological debate about inferential errors associated with p-values and statistical significance testing, readers are provided with a clear grasp of what statistical inference presupposes, and what it can and cannot do. To facilitate intuition, the representations throughout the book are as non-technical as possible. The central inspiration behind the text comes from the scientific debate about good statistical practices and the replication crisis. Calls for statistical reform include an unprecedented methodological warning from the American Statistical Association in 2016, a special issue “Statistical Inference in the 21st Century: A World Beyond p 0.05” of iThe American StatisticianNature in 2019. The book elucidates the probabilistic foundations and the potential of sample-based inferences, including random data generation, effect size estimation, and the assessment of estimation uncertainty caused by random error. Based on a thorough understanding of those basics, it then describes the p-value concept and the null-hypothesis-significance-testing ritual, and finally points out the ensuing inferential errors. This provides readers with the competence to avoid ill-guided statistical routines and misinterpretations of statistical quantities in the future. Intended for readers with an interest in understanding the role of statistical inference, the book provides a prudent assessment of the knowledge gain that can be obtained from a particular set of data under consideration of the uncertainty caused by random error. More particularly, it offers an accessible resource for graduate students as well as statistical practitioners who have a basic knowledge of statistics. Last but not least, it is aimed at scientists with a genuine methodological interest in the above-mentioned reform debate.
Openintro Statistics
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Author : David Diez
language : en
Publisher:
Release Date : 2015-07-02
Openintro Statistics written by David Diez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-02 with categories.
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
Third International Handbook Of Mathematics Education
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Author : M.A. (Ken) Clements
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-15
Third International Handbook Of Mathematics Education written by M.A. (Ken) Clements and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-15 with Mathematics categories.
The four sections in this Third International Handbook are concerned with: (a) social, political and cultural dimensions in mathematics education; (b) mathematics education as a field of study; (c) technology in the mathematics curriculum; and (d) international perspectives on mathematics education. These themes are taken up by 84 internationally-recognized scholars, based in 26 different nations. Each of section is structured on the basis of past, present and future aspects. The first chapter in a section provides historical perspectives (“How did we get to where we are now?”); the middle chapters in a section analyze present-day key issues and themes (“Where are we now, and what recent events have been especially significant?”); and the final chapter in a section reflects on policy matters (“Where are we going, and what should we do?”). Readership: Teachers, mathematics educators, ed.policy makers, mathematicians, graduate students, undergraduate students. Large set of authoritative, international authors.
Modes Of Representation In Developing Statistical Thinking In Education
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Author : Anastasiadou, Sofia D.
language : en
Publisher: IGI Global
Release Date : 2025-05-29
Modes Of Representation In Developing Statistical Thinking In Education written by Anastasiadou, Sofia D. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-29 with Education categories.
Developing the ability to understand and use multiple representations is vital for deepening students’ comprehension of statistical, probabilistic, and mathematical concepts. This skill enhances problem-solving by enabling learners to translate ideas across various forms, leading to more flexible and meaningful understanding. Representational competency is closely linked to communication, critical thinking, and the ability to engage with real-world data. Moreover, students’ attitudes, emotions, and self-confidence significantly influence their motivation and success in these subjects. Strengthening these aspects in education can lead to more effective learning experiences and greater long term achievement in math and statistics. Modes of Representation in Developing Statistical Thinking in Education explores different modes of representations in teaching and learning statistical, probabilistic notions, and attitudes in developing statistical thinking in education. By bringing together contributions from global experts, the volume fosters interdisciplinary collaboration, inspires new research directions, and provides the knowledge and tools necessary to navigate the evolving landscape of statistics education. Covering topics such as artificial intelligence, mathematics education, and web tools, this book is an excellent resource for researchers, academicians, educators, policymakers, data scientists, and more.