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Statistics Translated Second Edition
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Book Synopsis Statistics Translated by : Steven R. Terrell
Download or read book Statistics Translated written by Steven R. Terrell and published by Guilford Press. This book was released on 2012-03-29 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Statistics Translated, Second Edition, ISBN 978-1-4625-4540-7.
Book Synopsis Statistics Translated, Second Edition by : Steven R. Terrell
Download or read book Statistics Translated, Second Edition written by Steven R. Terrell and published by Guilford Publications. This book was released on 2021-03-08 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Roping the reader in with humor and real-world case examples presented as mysteries to be solved, this engaging text has been updated with new cases, the latest version of SPSS, and new coverage of multivariate analysis of variance. Steven R. Terrell prepares students and practitioners to become informed consumers of statistics so that they can make decisions based on data, and understand decisions others have made. He identifies six simple steps and guides readers to master them--from identifying a researchable problem to stating a hypothesis; identifying independent and dependent variables; and selecting, computing, and interpreting appropriate statistical tests. All techniques are demonstrated both manually and with the help of SPSS software. New to This Edition *All software instructions and examples are updated to SPSS Version 25. *Expanded chapter on the analysis of variance (ANOVA)--now covers multivariate ANOVA. *New and revised examples and quiz items pertaining to a broader range of fields, such as business, information systems, and medical sciences, along with education and psychology. Pedagogical Features *Examples of SPSS screenshots used for analyzing data. *User-friendly cautionary notes, "Putting it All Together" recaps, and alerts, such as "notice the effect size" or "check the direction of the mean scores." *End-of-chapter "Quiz Time" exercises that guide students to answer intriguing questions like whether working from home increases productivity, or whether age affects how long it takes to complete a doctoral degree. *Lists of key terms and formulas in each chapter, plus end-of-book glossary.
Book Synopsis An Introduction to Statistical Learning by : Gareth James
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Book Synopsis Statistical Rethinking by : Richard McElreath
Download or read book Statistical Rethinking written by Richard McElreath and published by CRC Press. This book was released on 2018-01-03 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Book Synopsis Applied Missing Data Analysis by : Craig K. Enders
Download or read book Applied Missing Data Analysis written by Craig K. Enders and published by Guilford Press. This book was released on 2010-04-23 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data.
Book Synopsis The Humongous Book of Statistics Problems by : Robert Donnelly
Download or read book The Humongous Book of Statistics Problems written by Robert Donnelly and published by Penguin. This book was released on 2009-12-01 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to solve statistics problems—and make them no problem! Most math and science study guides are dry and difficult, but this is the exception. Following the successful The Humongous Books in calculus and algebra, bestselling author Mike Kelley takes a typical statistics workbook, full of solved problems, and writes notes in the margins, adding missing steps and simplifying concepts and solutions. By learning how to interpret and solve problems as they are presented in statistics courses, students prepare to solve those difficult problems that were never discussed in class but are always on exams. There are also annotated notes throughout the book to clarify each problem—all guided by an author with a great track record for helping students and math enthusiasts. His website (calculus-help.com) reaches thousands of students every month.
Book Synopsis R for Statistics by : Pierre-Andre Cornillon
Download or read book R for Statistics written by Pierre-Andre Cornillon and published by CRC Press. This book was released on 2012-03-21 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples. Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R. Focusing on the R software, the first section covers: Basic elements of the R software and data processing Clear, concise visualization of results, using simple and complex graphs Programming basics: pre-defined and user-created functions The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including: Regression methods Analyses of variance and covariance Classification methods Exploratory multivariate analysis Clustering methods Hypothesis tests After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist. Datasets and all the results described in this book are available on the book’s webpage at http://www.agrocampus-ouest.fr/math/RforStat
Download or read book Statistics written by Michael J. Crawley and published by John Wiley & Sons. This book was released on 2005-05-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.
Book Synopsis Advanced High School Statistics by : David Diez
Download or read book Advanced High School Statistics written by David Diez and published by . This book was released on 2014-07-30 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: A free PDF copy of this textbook may be found on the project's website (do an online search for OpenIntro). This is a Preliminary Edition of a new textbook by OpenIntro that is focused on the advanced high school level.Chapters: 1 - Data Collection,2 - Summarizing Data,3 - Probability,4 - Distributions of Random Variables,5 - Foundation for Inference,6 - Inference for Categorical Data,7 - Inference for Numerical Data,8 - Introduction to Linear Regression.
Book Synopsis Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition by : Sorin Drăghici
Download or read book Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition written by Sorin Drăghici and published by CRC Press. This book was released on 2011-12-06 with total page 1092 pages. Available in PDF, EPUB and Kindle. Book excerpt: Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and rigorous description of powerful analysis techniques and algorithms for mining and interpreting biological information. Omitting tedious details, heavy formalisms, and cryptic notations, the text takes a hands-on, example-based approach that teaches students the basics of R and microarray technology as well as how to choose and apply the proper data analysis tool to specific problems. New to the Second Edition Completely updated and double the size of its predecessor, this timely second edition replaces the commercial software with the open source R and Bioconductor environments. Fourteen new chapters cover such topics as the basic mechanisms of the cell, reliability and reproducibility issues in DNA microarrays, basic statistics and linear models in R, experiment design, multiple comparisons, quality control, data pre-processing and normalization, Gene Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for all routines is available on an accompanying CD-ROM. With all the necessary prerequisites included, this best-selling book guides students from very basic notions to advanced analysis techniques in R and Bioconductor. The first half of the text presents an overview of microarrays and the statistical elements that form the building blocks of any data analysis. The second half introduces the techniques most commonly used in the analysis of microarray data.
Book Synopsis Probability and Statistics with Reliability, Queuing, and Computer Science Applications by : Kishor S. Trivedi
Download or read book Probability and Statistics with Reliability, Queuing, and Computer Science Applications written by Kishor S. Trivedi and published by John Wiley & Sons. This book was released on 2016-06-30 with total page 1042 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applications Second edition now also available in Paperback. This updated and revised edition of the popular classic first edition relates fundamental concepts in probability and statistics to the computer sciences and engineering. The author uses Markov chains and other statistical tools to illustrate processes in reliability of computer systems and networks, fault tolerance, and performance. This edition features an entirely new section on stochastic Petri nets—as well as new sections on system availability modeling, wireless system modeling, numerical solution techniques for Markov chains, and software reliability modeling, among other subjects. Extensive revisions take new developments in solution techniques and applications into account and bring this work totally up to date. It includes more than 200 worked examples and self-study exercises for each section. Probability and Statistics with Reliability, Queuing and Computer Science Applications, Second Edition offers a comprehensive introduction to probability, stochastic processes, and statistics for students of computer science, electrical and computer engineering, and applied mathematics. Its wealth of practical examples and up-to-date information makes it an excellent resource for practitioners as well. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Book Synopsis Encyclopedia of Data Warehousing and Mining, Second Edition by : Wang, John
Download or read book Encyclopedia of Data Warehousing and Mining, Second Edition written by Wang, John and published by IGI Global. This book was released on 2008-08-31 with total page 2542 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.
Book Synopsis Statistical Power Analysis for the Behavioral Sciences by : Jacob Cohen
Download or read book Statistical Power Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-05-13 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author :Kathleen M. White, PhD, RN, NEA-BC, FAAN Publisher :Springer Publishing Company ISBN 13 :082611783X Total Pages :472 pages Book Rating :4.8/5 (261 download)
Book Synopsis Translation of Evidence into Nursing and Health Care, Second Edition by : Kathleen M. White, PhD, RN, NEA-BC, FAAN
Download or read book Translation of Evidence into Nursing and Health Care, Second Edition written by Kathleen M. White, PhD, RN, NEA-BC, FAAN and published by Springer Publishing Company. This book was released on 2016-03-17 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed as a textbook for the DNP curriculum and as a practical resource for more seasoned health professionals, this acclaimed text encompasses an interprofessional approach to translating evidence into nursing and health care practice that is useful for both clinical and nonclinical environments. The second edition presents new chapters, three of which feature additional approaches for translating evidence into practice, new methods of information technology for translation, and interprofessional collaboration and practice for translation and three that offer 19 exemplars that illustrate actual translation work within the areas of population health and specialty practice, and in the health care system. Consistently woven throughout are the themes of integration and application of knowledge into practice, leadership and evaluating change, leadership strategies for translation, and interprofessional applications across settings. Also included is new information about outcomes management for improvement of direct and indirect care. The second edition continues to deliver applicable theory and strategies to achieve improved outcomes, and meets the DNP core competency requirements. It features a variety of models for change as they relate to translation of research into practice. The text underscores the importance of translating evidence for use in practice to improve health care and health care delivery, and presents strategies to achieve this. It addresses the use of evidence to improve nursing education, discusses how to reduce the divide between researchers and policy makers, and presents expedients for overcoming resistance to change. Extensive lists of references, web links, and other resources enhance learning and support the development of the DNP core competencies. NEW TO THE SECOND EDITION: Addition of an esteemed co-editor Reorganized and revised for enhanced comprehension New chapters: Methods for Translation, Information Technology and Decision Support, Interprofessional Collaboration and Practice for Translation, and Data Management and Evaluation of Translation Three new exemplar chapters: Population Health Exemplars, Specialty Practice Exemplars, and Health Care System Exemplars Updated information on integration and application of knowledge into practice, leading and evaluating change, leadership strategies for translation, and interprofessional application across settings New coverage of outcomes management for improvement of direct and indirect care KEY FEATURES: Offers an in-depth guide for planning, implementing, and translating evidence Includes extensive references necessary for doctoral study Provides the perfect supplement for evidence-based practice materials that often have limited information or value for translation/implementation activities
Book Synopsis Monte Carlo Statistical Methods by : Christian Robert
Download or read book Monte Carlo Statistical Methods written by Christian Robert and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.
Book Synopsis OpenIntro Statistics by : David Diez
Download or read book OpenIntro Statistics written by David Diez and published by . This book was released on 2015-07-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
