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The fourth edition of this popular book by Jessica Utts develops statistical literacy and critical thinking through real-world applications, with an emphasis on ideas, not calculations. This text focuses on the key concepts that educated citizens need to know about statistics. These ideas are introduced in interesting applied and real contexts, without using an abundance of technicalities and calculations that only serve to confuse students. NEW for Fall 2020 - Turn your students into statistical thinkers with the Statistical Analysis and Learning Tool (SALT). SALT is an easy-to-use data analysis tool created with the intro-level student in mind. It contains dynamic graphics and allows students to manipulate data sets in order to visualize statistics and gain a deeper conceptual understanding about the meaning behind data. SALT is built by Cengage, comes integrated in Cengage WebAssign Statistics courses and available to use standalone. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Student CD-ROM contains lab manuals, applets, data sets, presentation slides, Web resources, and tutorial quiz; Interactive video skillbuilder CD-ROM contains video instruction on key examples from the text.
This series of resources provides comprehensive support for the Framework for Teaching Mathematics for Year 8, with particular emphasis on a three part mathematics lesson. The materials are fully linked to Key Maths and address the beginning and end of the typical lesson structure outlined in the Framework. The activities within the packs provide a variety of presentational models including opportunities for interactive oral work, direct teaching and paired or group activity work to encourage pupils to engage in mathematical conversation. This ICT resource pack provides full details on developing and supporting ICT work in mathematics. Full range of additional worksheets that build on the activities in the CD-ROM and linked to the National Curriculum. The pack makes full reference to DfEE ICT guidelines and other requirements.
Bringing together relevant statistical and probabilistic techniques, a practical manual for advanced undergraduate and graduate students and professional astronomers.
FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides students with an understanding of the logic behind the statistics, so they understand why and how certain methods are used -- rather than simply carry out techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. Written in an informal style, the text provides an abundance of real data and research studies that provide a real-life perspective and help students learn and understand concepts. In alignment with current trends in statistics in the behavioral sciences, the text emphasizes effect sizes and meta-analysis, and integrates frequent demonstrations of computer analyses through SPSS and R. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
"Using real data, the authors show you how statistical techniques are used with increasing frequency in a variety of fields, including business, medicine, social sciences, and applied sciences such as engineering. Their accessible writing style is enhanced by numerous examples, including hands-on activities and "Seeing Statistics" applets."--Publisher description.
In most countries, only very limited time resources are available for statistics education within mathematics education. Thus, statistics education research needs to develop teaching-learning arrangements that are compact and applicable to classrooms. Christian Büscher designs and investigates a compact teaching-learning arrangement which aims at mathematical and reflective knowledge about statistics. Central results include the specification of the learning content of statistical measures, an empirical reconstruction of students’ learning processes towards statistical measures, and the identification of students’ situated reflections about mathematics within their learning processes.
The audience remains much the same as for the 1992 Handbook, namely, mathematics education researchers and other scholars conducting work in mathematics education. This group includes college and university faculty, graduate students, investigators in research and development centers, and staff members at federal, state, and local agencies that conduct and use research within the discipline of mathematics. The intent of the authors of this volume is to provide useful perspectives as well as pertinent information for conducting investigations that are informed by previous work. The Handbook should also be a useful textbook for graduate research seminars. In addition to the audience mentioned above, the present Handbook contains chapters that should be relevant to four other groups: teacher educators, curriculum developers, state and national policy makers, and test developers and others involved with assessment. Taken as a whole, the chapters reflects the mathematics education research community's willingness to accept the challenge of helping the public understand what mathematics education research is all about and what the relevance of their research fi ndings might be for those outside their immediate community.
This book reveals the development of students' understanding of statistical literacy. It provides a way to "see" student thinking and gives readers a deeper sense of how students think about important statistical topics. Intended as a complement to curriculum documents and textbook series, it is consistent with the current principles and standards of the National Council of Teachers of Mathematics. The term "statistical literacy" is used to emphasize that the purpose of the school curriculum should not be to turn out statisticians but to prepare statistically literate school graduates who are prepared to participate in social decision making. Based on ten years of research--with reference to other significant research as appropriate--the book looks at students' thinking in relation to tasks based on sampling, graphical representations, averages, chance, beginning inference, and variation, which are essential to later work in formal statistics. For those students who do not proceed to formal study, as well as those who do, these concepts provide a basis for decision making or questioning when presented with claims based on data in societal settings. Statistical Literacy at School: Growth and Goals: *establishes an overall framework for statistical literacy in terms of both the links to specific school curricula and the wider appreciation of contexts within which chance and data-handling ideas are applied; *demonstrates, within this framework, that there are many connections among specific ideas and constructs; *provides tasks, adaptable for classroom or assessment use, that are appropriate for the goals of statistical literacy; *presents extensive examples of student performance on the tasks, illustrating hierarchies of achievement, to assist in monitoring gains and meeting the goals of statistical literacy; and *includes a summary of analysis of survey data that suggests a developmental hierarchy for students over the years of schooling with respect to the goal of statistical literacy. Statistical Literacy at School: Growth and Goals is directed to researchers, curriculum developers, professionals, and students in mathematics education as well those across the curriculum who are interested in students' cognitive development within the field; to teachers who want to focus on the concepts involved in statistical literacy without the use of formal statistical techniques; and to statisticians who are interested in the development of student understanding before students are exposed to the formal study of statistics.