Workshop Statistics:

Discovery With Data and Minitab

Author: Allan J. Rossman,Beth L. Chance

Publisher: Springer Science & Business Media

ISBN: 147572926X

Category: Mathematics

Page: 486

View: 2471

Shorn of all subtlety and led naked out of the protec tive fold of educational research literature, there comes a sheepish little fact: lectures don't work nearly as well as many of us would like to think. -George Cobb (1992) This book contains activities that guide students to discover statistical concepts, explore statistical principles, and apply statistical techniques. Students work toward these goals through the analysis of genuine data and through inter action with one another, with their instructor, and with technology. Providing a one-semester introduction to fundamental ideas of statistics for college and advanced high school students, Warkshop Statistics is designed for courses that employ an interactive learning environment by replacing lectures with hands on activities. The text contains enough expository material to stand alone, but it can also be used to supplement a more traditional textbook. Some distinguishing features of Workshop Statistics are its emphases on active learning, conceptual understanding, genuine data, and the use of technology. The following sections of this preface elaborate on each of these aspects and also describe the unusual organizational structure of this text.
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Workshop Statistics

Discovery with Data and Fathom

Author: Allan J. Rossman,Beth L. Chance,Robin H. Lock,Workshop Mathematics Project

Publisher: Springer Science & Business Media

ISBN: 9781930190085

Category: Mathematics

Page: 654

View: 2420

Workshop statistics: discovery with data and fathom integrates instructions specific to Fathom while retaining all the distinctive features of the original text. Fathom is an open-format statistical learning environment that allows dynamic manipulation developing conceptual and graphical understanding, as well as for most standard computational tasks. This text focuses on probability and the Bayesian view point. It presents basic material of probability and the introduces inference by means of Bayensian rules. The emphasis of the book is on statistical thinking and how one learns from data.
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Workshop Statistics: Discovery with Data, 4th Edition

Discovery with Data and Fathom

Author: Allan J. Rossman

Publisher: Wiley Global Education

ISBN: 1118213424

Category: Mathematics

Page: 752

View: 6871

Allan Rossman's 4th Edition of Workshop Statistics: Discovery with Data, is enhanced from previous issues with more focus and emphasis on collaborative learning. It further requires student observation, and integrates technology for gathering, recording, and synthesizing data. The text offers more flexibility in selecting technology tools for classrooms primarily using technologies other than graphing calculators or FathomTM Dynamic Data software. Furthermore, it presents more standards for teaching statistics in an innovative, investigative, and accessible as well as provides in-depth guidance and resources to support active learning of statistics and includes updated real data sets with everyday applications in order to promote statistical literacy.
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Workshop Statistics

Discovery with Data

Author: Allan J. Rossman,Beth L. Chance

Publisher: Wiley

ISBN: 9780470607657

Category: Mathematics

Page: 688

View: 5151

This text is an unbound, binder-ready edition. Allan Rossman's 4th Edition of Workshop Statistics: Discovery with Data, Binder Ready Version is enhanced from previous issues with more focus and emphasis on collaborative learning. It further requires student observation, and integrates technology for gathering, recording, and synthesizing data. The text offers more flexibility in selecting technology tools for classrooms primarily using technologies other than graphing calculators or Fathom Dynamic Data software. Furthermore, it presents more standards for teaching statistics in an innovative, investigative, and accessible as well as provides in-depth guidance and resources to support active learning of statistics and includes updated real data sets with everyday applications in order to promote statistical literacy.
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Workshop Statistics

Discovery with Data, A Bayesian Approach

Author: James H. Albert,Jim Albert,Allan J. Rossman

Publisher: Springer Science & Business Media

ISBN: 9781930190122

Category: Mathematics

Page: 532

View: 4658

The "workshop approach" builds upon analysis of genuine data and leads to practical working experience. Unique in its format, the text allows students to discover statistical concepts, explore statistical principles, and apply statistical techniques. The book, in addition to the numerous activities and exercises around which the text is built, includes basic text exposition for each topic, concept "wrap-ups", and data appendices. Among the many features are an emphasis on Bayesian techniques, which focus on the concept of statistical inference.
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Workshop Statistics

Discovery with Data SPSS Companion

Author: A. J. Rossman

Publisher: N.A

ISBN: 9780470484579

Category: SPSS (Computer file)

Page: 184

View: 7299

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Workshop Statistics, with Student CD and Access

Discovery with Data

Author: Allan J. Rossman,Beth L. Chance

Publisher: Wiley

ISBN: 9780470413487

Category: Mathematics

Page: 660

View: 9386

The Workshop Statistics™ series has set a standard for teaching statistics in an innovative, investigative, and accessible manner for introductory college courses, as well as for the high school statistics classroom, including AP® Statistics. In its third edition, Workshop Statistics: Discovery with Data continues to emphasize collaborative learning, require student observation, and integrate technology for gathering, recording, and synthesizing data. The third edition provides even more guidance and resources for students to support their active learning of statistics and includes updated real data sets with everyday applications in order to promote statistical literacy. This version of the text provides the most flexibility in selecting technology tools and is recommended for classrooms primarily using technologies other than graphing calculators or Fathom™ Dynamic Data software.
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Workshop Statistics, Discovery with Data and Fathom

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1467270431

Category: Education

Page: 63

View: 4564

Facts101 is your complete guide to Workshop Statistics, Discovery with Data and Fathom. 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.
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Workshop Statistics , Discovery With Data

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1467270407

Category: Education

Page: 54

View: 1746

Facts101 is your complete guide to Workshop Statistics , Discovery With Data. 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.
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Bayesian Computation with R

Author: Jim Albert

Publisher: Springer Science & Business Media

ISBN: 0387922989

Category: Mathematics

Page: 300

View: 4124

There has been dramatic growth in the development and application of Bayesian inference in statistics. Berger (2000) documents the increase in Bayesian activity by the number of published research articles, the number of books,andtheextensivenumberofapplicationsofBayesianarticlesinapplied disciplines such as science and engineering. One reason for the dramatic growth in Bayesian modeling is the availab- ity of computational algorithms to compute the range of integrals that are necessary in a Bayesian posterior analysis. Due to the speed of modern c- puters, it is now possible to use the Bayesian paradigm to ?t very complex models that cannot be ?t by alternative frequentist methods. To ?t Bayesian models, one needs a statistical computing environment. This environment should be such that one can: write short scripts to de?ne a Bayesian model use or write functions to summarize a posterior distribution use functions to simulate from the posterior distribution construct graphs to illustrate the posterior inference An environment that meets these requirements is the R system. R provides a wide range of functions for data manipulation, calculation, and graphical d- plays. Moreover, it includes a well-developed, simple programming language that users can extend by adding new functions. Many such extensions of the language in the form of packages are easily downloadable from the Comp- hensive R Archive Network (CRAN).
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Refining the Concept of Scientific Inference When Working with Big Data

Proceedings of a Workshop

Author: National Academies of Sciences, Engineering, and Medicine,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics

Publisher: National Academies Press

ISBN: 0309454441

Category: Mathematics

Page: 114

View: 3662

The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.
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In the Deep Heart's Core

Author: Michael Johnston,Robert Coles

Publisher: Grove Press

ISBN: 9780802140241

Category: Education

Page: 240

View: 2695

A Teach for America volunteer recounts his own tenuous education as well as his tenure in the rural Mississippi Delta, one of the poorest districts in the country, during which he encountered fierce racial divisions, drug problems, and gang violence. Reprint.
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Statistical Learning with Sparsity

The Lasso and Generalizations

Author: Trevor Hastie,Robert Tibshirani,Martin Wainwright

Publisher: CRC Press

ISBN: 1498712177

Category: Business & Economics

Page: 367

View: 7695

Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data. Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of l1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso. In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.
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The Future of Scientific Knowledge Discovery in Open Networked Environments:

Summary of a Workshop

Author: Board on Research Data and Information,Policy and Global Affairs,National Research Council

Publisher: National Academies Press

ISBN: 0309267919

Category: Science

Page: 185

View: 670

Digital technologies and networks are now part of everyday work in the sciences, and have enhanced access to and use of scientific data, information, and literature significantly. They offer the promise of accelerating the discovery and communication of knowledge, both within the scientific community and in the broader society, as scientific data and information are made openly available online. The focus of this project was on computer-mediated or computational scientific knowledge discovery, taken broadly as any research processes enabled by digital computing technologies. Such technologies may include data mining, information retrieval and extraction, artificial intelligence, distributed grid computing, and others. These technological capabilities support computer-mediated knowledge discovery, which some believe is a new paradigm in the conduct of research. The emphasis was primarily on digitally networked data, rather than on the scientific, technical, and medical literature. The meeting also focused mostly on the advantages of knowledge discovery in open networked environments, although some of the disadvantages were raised as well. The workshop brought together a set of stakeholders in this area for intensive and structured discussions. The purpose was not to make a final declaration about the directions that should be taken, but to further the examination of trends in computational knowledge discovery in the open networked environments, based on the following questions and tasks: 1. Opportunities and Benefits: What are the opportunities over the next 5 to 10 years associated with the use of computer-mediated scientific knowledge discovery across disciplines in the open online environment? What are the potential benefits to science and society of such techniques? 2. Techniques and Methods for Development and Study of Computer-mediated Scientific Knowledge Discovery: What are the techniques and methods used in government, academia, and industry to study and understand these processes, the validity and reliability of their results, and their impact inside and outside science? 3. Barriers: What are the major scientific, technological, institutional, sociological, and policy barriers to computer-mediated scientific knowledge discovery in the open online environment within the scientific community? What needs to be known and studied about each of these barriers to help achieve the opportunities for interdisciplinary science and complex problem solving? 4. Range of Options: Based on the results obtained in response to items 1-3, define a range of options that can be used by the sponsors of the project, as well as other similar organizations, to obtain and promote a better understanding of the computer-mediated scientific knowledge discovery processes and mechanisms for openly available data and information online across the scientific domains. The objective of defining these options is to improve the activities of the sponsors (and other similar organizations) and the activities of researchers that they fund externally in this emerging research area. The Future of Scientific Knowledge Discovery in Open Networked Environments: Summary of a Workshop summarizes the responses to these questions and tasks at hand.
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AP Statistics

Preparing for the Advanced Placement Exam

Author: James F. Bohan,Beth Chance

Publisher: Perfection Learning

ISBN: 9781567655810

Category: Juvenile Nonfiction

Page: 400

View: 3878

To help students develop the skills and strategies needed to succeed on the AP Statisitcs examination.
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