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Author: Phillip I. Good Publisher: John Wiley & Sons ISBN: 0471722499 Category : Mathematics Languages : en Pages : 244
Book Description
Stimulate learning through discovery With its emphasis on the discovery method, this book allows readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers will quickly master and learn to apply statistical methods, such as bootstrap, decision trees, and permutations, to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: Tests and estimation procedures for one, two, and multiple samples Model building Multivariate analysis Complex experimental design Throughout the text, the R programming language is used to illustrate new concepts and assist readers in completing exercises. Readers may download the freely available R programming language from the Internet or take advantage of the menu-driven S-PLUS® program. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: More than two hundred exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills Companion FTP site provides access to all data sets and programs discussed in the text Dozens of thought-provoking questions in the final chapter, Problem Solving, assist readers in applying statistics to address real-life problems Instructor's manual provides answers to exercises Helpful appendices include an introduction to S-PLUS® features This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited for both students and practitioners.
Author: Phillip I. Good Publisher: John Wiley & Sons ISBN: 0471722499 Category : Mathematics Languages : en Pages : 244
Book Description
Stimulate learning through discovery With its emphasis on the discovery method, this book allows readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers will quickly master and learn to apply statistical methods, such as bootstrap, decision trees, and permutations, to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: Tests and estimation procedures for one, two, and multiple samples Model building Multivariate analysis Complex experimental design Throughout the text, the R programming language is used to illustrate new concepts and assist readers in completing exercises. Readers may download the freely available R programming language from the Internet or take advantage of the menu-driven S-PLUS® program. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: More than two hundred exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills Companion FTP site provides access to all data sets and programs discussed in the text Dozens of thought-provoking questions in the final chapter, Problem Solving, assist readers in applying statistics to address real-life problems Instructor's manual provides answers to exercises Helpful appendices include an introduction to S-PLUS® features This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited for both students and practitioners.
Author: Phillip I. Good Publisher: John Wiley & Sons ISBN: 1118428218 Category : Mathematics Languages : en Pages : 224
Book Description
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
Author: John B.H. Birks Publisher: Springer Science & Business Media ISBN: 9400727445 Category : Science Languages : en Pages : 751
Book Description
Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.
Author: H. John B. Birks Publisher: Springer Science & Business Media ISBN: 9400727453 Category : Science Languages : en Pages : 751
Book Description
Numerical and statistical methods have rapidly become part of a palaeolimnologist’s tool-kit. They are used to explore and summarise complex data, reconstruct past environmental variables from fossil assemblages, and test competing hypotheses about the causes of observed changes in lake biota through history. This book brings together a wide array of numerical and statistical techniques currently available for use in palaeolimnology and other branches of palaeoecology. Visit http://extras.springer.com the Springer's Extras website to view data-sets, figures, software, and R scripts used or mentioned in this book.
Author: Fortunato Pesarin Publisher: John Wiley & Sons ISBN: 9780470689523 Category : Mathematics Languages : en Pages : 448
Book Description
Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies. The Authors give a general overview on permutation tests with a focus on recent theoretical advances within univariate and multivariate complex permutation testing problems, this book brings the reader completely up to date with today’s current thinking. Key Features: Examines the most up-to-date methodologies of univariate and multivariate permutation testing. Includes extensive software codes in MATLAB, R and SAS, featuring worked examples, and uses real case studies from both experimental and observational studies. Includes a standalone free software NPC Test Release 10 with a graphical interface which allows practitioners from every scientific field to easily implement almost all complex testing procedures included in the book. Presents and discusses solutions to the most important and frequently encountered real problems in multivariate analyses. A supplementary website containing all of the data sets examined in the book along with ready to use software codes. Together with a wide set of application cases, the Authors present a thorough theory of permutation testing both with formal description and proofs, and analysing real case studies. Practitioners and researchers, working in different scientific fields such as engineering, biostatistics, psychology or medicine will benefit from this book.
Author: Markus Neuhauser Publisher: CRC Press ISBN: 1439867046 Category : Mathematics Languages : en Pages : 247
Book Description
Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. Th
Author: Robert Bartoszynski Publisher: John Wiley & Sons ISBN: 1119243823 Category : Mathematics Languages : en Pages : 592
Book Description
Updated classic statistics text, with new problems and examples Probability and Statistical Inference, Third Edition helps students grasp essential concepts of statistics and its probabilistic foundations. This book focuses on the development of intuition and understanding in the subject through a wealth of examples illustrating concepts, theorems, and methods. The reader will recognize and fully understand the why and not just the how behind the introduced material. In this Third Edition, the reader will find a new chapter on Bayesian statistics, 70 new problems and an appendix with the supporting R code. This book is suitable for upper-level undergraduates or first-year graduate students studying statistics or related disciplines, such as mathematics or engineering. This Third Edition: Introduces an all-new chapter on Bayesian statistics and offers thorough explanations of advanced statistics and probability topics Includes 650 problems and over 400 examples - an excellent resource for the mathematical statistics class sequence in the increasingly popular "flipped classroom" format Offers students in statistics, mathematics, engineering and related fields a user-friendly resource Provides practicing professionals valuable insight into statistical tools Probability and Statistical Inference offers a unique approach to problems that allows the reader to fully integrate the knowledge gained from the text, thus, enhancing a more complete and honest understanding of the topic.
Author: Phillip I. Good Publisher: Springer Science & Business Media ISBN: 081764444X Category : Mathematics Languages : en Pages : 229
Book Description
This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
Author: Sue Ellen Haupt Publisher: Springer Science & Business Media ISBN: 1402091192 Category : Science Languages : en Pages : 418
Book Description
How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.
Author: Patricia A. Alexander Publisher: Routledge ISBN: 1135283516 Category : Education Languages : en Pages : 2419
Book Description
Sponsored by Division 15 of APA, the second edition of this groundbreaking book has been expanded to 41 chapters that provide unparalleled coverage of this far-ranging field. Internationally recognized scholars contribute up-to-date reviews and critical syntheses of the following areas: foundations and the future of educational psychology, learners’ development, individual differences, cognition, motivation, content area teaching, socio-cultural perspectives on teaching and learning, teachers and teaching, instructional design, teacher assessment, and modern perspectives on research methodologies, data, and data analysis. New chapters cover topics such as adult development, self-regulation, changes in knowledge and beliefs, and writing. Expanded treatment has been given to cognition, motivation, and new methodologies for gathering and analyzing data. The Handbook of Educational Psychology, Second Edition provides an indispensable reference volume for scholars, teacher educators, in-service practitioners, policy makers and the academic libraries serving these audiences. It is also appropriate for graduate level courses devoted to the study of educational psychology.
Author: Phillip I. Good
Author: Phillip I. Good
Author: Phillip I. Good
Author: John B.H. Birks
Author: H. John B. Birks
Author: Fortunato Pesarin
Author: Markus Neuhauser
Author: Robert Bartoszynski
Author: Phillip I. Good
Author: Sue Ellen Haupt
Author: Patricia A. Alexander