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OverviewFilled with practical learning activities to adopt within your classroom, The Learning and Teaching of Statistics and Probability places reasoning about quantities and quantification at the core of learning and teaching statistics. A companion website to this book is also available at https://neilhatfield.github.io/IMPACT_Statistics/, allowing readers to access a directory of resources – data collections and web-based applets – used in some of the instructional activities featured within this book. Through its presentation of conceptual analyses and resources for teaching with statistical data, the book’s five chapters establish key concepts and foundational ideas in statistics and probability, emphasizing the development of learner understanding and coherence, for example: Individual cases and their attributes Data collections, sub-collections, and relevant operations to quantify their attributes Samples, population, and quantifying variation Types of processes, meanings of randomness, and probability as a measure of stochastic tendency Sampling distributions and statistical inference. This highly informative yet practical book is an indispensable resource for teachers of secondary school mathematics, mathematics subject leads, and mathematics and statistics educators within the wider field of education. Full Product DetailsAuthor: Luis Saldanha (L’Université du Québec à Montréal, Canada) , Neil J. Hatfield (Pennsylvania State University, USA) , Egan J Chernoff (University of Saskatchewan, Canada) , Caterina PrimiPublisher: Taylor & Francis Ltd Imprint: Routledge Weight: 0.360kg ISBN: 9780367654863ISBN 10: 0367654865 Pages: 152 Publication Date: 08 December 2023 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsIntroduction; 1. Individual Cases, Attributes, and Data; 2. Collections of Cases, Attributes of Collections, and Measures of Such Attributes; 3. Samples, Populations, and Quantifying their Variation; 4. Processes, Randomness, and Probability; 5. Sampling Distributions and Statistical Inference; Appendix; IndexReviews"""This book definitely makes me think about the ways we normally talk about statistics with our students and our prospective teachers, and that perhaps there are alternative ways for us to introduce data, statistics, and inference than many of us do now. The authors are right-on with their path: Cases--> Collections--> Samples--> Distributions. I applaud that, and also their excellent ""mini"" and ""integrating"" activities that they have included throughout the book to get us all thinking and reasoning about quantities in statistics."" J. Michael Shaughnessy, Professor Emeritus in Mathematics and Statistics at Portland State University." """This book definitely makes me think about the ways we normally talk about statistics with our students and our prospective teachers, and that perhaps there are alternative ways for us to introduce data, statistics, and inference than many of us do now. The authors are right-on with their path: Cases--> Collections--> Samples--> Distributions. I applaud that, and also their excellent ""mini"" and ""integrating"" activities that they have included throughout the book to get us all thinking and reasoning about quantities in statistics."" J. Michael Shaugnessy, Professor Emeritus in Mathematics and Statistics at Portland State University." Author InformationLuis Saldanha is a professor of Didactics of Mathematics in the department of mathematics at l’Université du Québec à Montréal, Canada. His research focuses on mathematical thinking, specifically the development of students’ statistical reasoning in relation to their engagement with instruction designed to foster their understanding of statistical concepts. Neil J. Hatfield is an assistant research professor in the Department of Statistics at Pennsylvania State University, U.S.A. His main research interests focus on cognition related to the concept of distribution; the teaching of statistics, data science, and probability; and diversity, equity, and inclusion in STEM. Egan J. Chernoff is a professor of Mathematics Education at the University of Saskatchewan, Canada. His editorial affiliations include Statistics Education Research Journal; The Mathematics Enthusiast; Mathematical Thinking and Learning; Journal of Mathematical Behavior; Canadian Journal of Science, Mathematics, and Technology Education; and more. Caterina Primi is a full professor in Psicometria at the Faculty of Psychology at the University of Florence, Italy. She is an experienced teacher of graduate, post-graduate, and PhD level courses in statistics, research methods, and psychological testing. Tab Content 6Author Website:Countries AvailableAll regions |