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Discovering Statistics Using R


Discovering Statistics Using R
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Discovering Statistics Using R


Discovering Statistics Using R
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Author : Andy Field
language : en
Publisher: SAGE
Release Date : 2012-03-07

Discovering Statistics Using R written by Andy Field and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-07 with Reference categories.


Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field′s books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you′re doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect. Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more. Given this book′s accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.



Discovering Statistics Using Ibm Spss Statistics


Discovering Statistics Using Ibm Spss Statistics
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Author : Andy Field
language : en
Publisher: SAGE
Release Date : 2017-11-14

Discovering Statistics Using Ibm Spss Statistics written by Andy Field and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-14 with Social Science categories.


With an exciting new look, new characters to meet, and its unique combination of humour and step-by-step instruction, this award-winning book is the statistics lifesaver for everyone. From initial theory through to regression, factor analysis and multilevel modelling, Andy Field animates statistics and SPSS software with his famously bizarre examples and activities. What’s brand new: A radical new design with original illustrations and even more colour A maths diagnostic tool to help students establish what areas they need to revise and improve on. A revamped online resource that uses video, case studies, datasets, testbanks and more to help students negotiate project work, master data management techniques, and apply key writing and employability skills New sections on replication, open science and Bayesian thinking Now fully up to date with latest versions of IBM SPSS Statistics©. All the online resources above (video, case studies, datasets, testbanks) can be easily integrated into your institution′s virtual learning environment or learning management system. This allows you to customize and curate content for use in module preparation, delivery and assessment. Please note that ISBN: 9781526445780 comprises the paperback edition of the Fifth Edition and the student version of IBM SPSS Statistics.



Understanding Statistics Using R


Understanding Statistics Using R
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Author : Randall Schumacker
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-24

Understanding Statistics Using R written by Randall Schumacker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-24 with Computers categories.


This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials. The book contains R script programs to demonstrate important topics and concepts covered in a statistics course, including probability, random sampling, population distribution types, role of the Central Limit Theorem, creation of sampling distributions for statistics, and more. The chapters contain T/F quizzes to test basic knowledge of the topics covered. In addition, the book chapters contain numerous exercises with answers or solutions to the exercises provided. The chapter exercises reinforce an understanding of the statistical concepts presented in the chapters. An instructor can select any of the supplemental materials to enhance lectures and/or provide additional coverage of concepts and topics in their statistics book.



Discovering Statistics Using Ibm Spss Statistics


Discovering Statistics Using Ibm Spss Statistics
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Author : Andy Field
language : en
Publisher: SAGE
Release Date : 2013-01-24

Discovering Statistics Using Ibm Spss Statistics written by Andy Field and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-24 with Social Science categories.


Unrivalled in the way it makes the teaching of statistics compelling and accessible to even the most anxious of students, the only statistics textbook you and your students will ever need just got better! Andy Field's comprehensive and bestselling Discovering Statistics Using SPSS 4th Edition takes students from introductory statistical concepts through very advanced concepts, incorporating SPSS throughout. The Fourth Edition focuses on providing essential content updates, better accessibility to key features, more instructor resources, and more content specific to select disciplines. It also incorporates powerful new digital developments on the textbook's companion website (visit sagepub.com for more information). WebAssign® The Fourth Edition will be available on WebAssign, allowing instructors to produce and manage assignments with their studnets online using a grade book that allows them to track and monitor students' progress. Students receive unlimited practice using a combination of approximately 2000 multiple choice and algorithmic questions. WebAssign provided students with instant feedback and links directly to the accompanying eBook section where the concept was covered, allowing students to find the correct solution. SAGE MobileStudy SAGE MobileStudy allows students equipped with smartphones and tablets to access select material, such as Cramming Sam's Study Tips, anywhere they receive mobile service. With QR codes included throughout the text, it's easy for students to get right to the section they need to study, allowing them to continue their study from virtually anywhere, even when they are away from thier printed copy of the text. Visit the publisher's website to preview the MobileStudy site. Education and Sport Sciences instructor support materials with enhanced ones for Psychology, Business and Management and the Health sciences make the book even more relevant to a wider range of subjects across the social sciences and where statistics is taught to a cross-disciplinary audience. Major Updates to the 4th Edition Fully compatible with recent SPSS releases up to and including version 20.0 Exciting new characters, including statistical cult leader Oditi, who provides students access to interesting and helpful video clips to illustrate statistical and SPSS concepts, and Confusious, who helps students clarify confusing quantitative terminology New discipline specific support matierlas have been added for Education, Sports Sciences, Psychology, Business & Management, and Health Sciences, making the book even more relevant to a wider range of subjects across the Social, Behavioral, and Health Sciences is taught to an interdisciplinary audience. An enhanced Companion Website (visit the publisher's website for more information) offers a wealth of material that can be used in conjunction with the textbook, including: PowerPoints Testbanks Answers to the Smart Alex tasks at the end of each chapter Datafiles for testing problems in SPSS Flashcards of key concepts Self-assessment multiple-choice questions Online videos of key statistical and SPSS procedures



Statistics


Statistics
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Author : Michael J. Crawley
language : en
Publisher: John Wiley & Sons
Release Date : 2005-05-06

Statistics written by Michael J. Crawley and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-06 with Mathematics categories.


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.



R For Statistics


R For Statistics
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Author : Pierre-Andre Cornillon
language : en
Publisher: CRC Press
Release Date : 2012-03-21

R For Statistics written by Pierre-Andre Cornillon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-21 with Mathematics categories.


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



Discovering Statistics Using Spss For Windows


Discovering Statistics Using Spss For Windows
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Author : Andy P. Field
language : en
Publisher: SAGE
Release Date : 2000

Discovering Statistics Using Spss For Windows written by Andy P. Field and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Social Science categories.


Andy Field draws on his experience of teaching advanced statistics to extend existing SPSS windows texts to a higher level. He covers ANOVA, MANOVA, logistic regression, comparing means tests and factor analysis.



Data Science In Education Using R


Data Science In Education Using R
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Author : Ryan A. Estrellado
language : en
Publisher: Routledge
Release Date : 2020-10-26

Data Science In Education Using R written by Ryan A. Estrellado and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-26 with Education categories.


Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.



A Tiny Handbook Of R


A Tiny Handbook Of R
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Author : Mike Allerhand
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-25

A Tiny Handbook Of R written by Mike Allerhand and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-25 with Computers categories.


This Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.



The Big R Book


The Big R Book
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Author : Philippe J. S. De Brouwer
language : en
Publisher: John Wiley & Sons
Release Date : 2020-10-27

The Big R Book written by Philippe J. S. De Brouwer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-27 with Mathematics categories.


Introduces professionals and scientists to statistics and machine learning using the programming language R Written by and for practitioners, this book provides an overall introduction to R, focusing on tools and methods commonly used in data science, and placing emphasis on practice and business use. It covers a wide range of topics in a single volume, including big data, databases, statistical machine learning, data wrangling, data visualization, and the reporting of results. The topics covered are all important for someone with a science/math background that is looking to quickly learn several practical technologies to enter or transition to the growing field of data science. The Big R-Book for Professionals: From Data Science to Learning Machines and Reporting with R includes nine parts, starting with an introduction to the subject and followed by an overview of R and elements of statistics. The third part revolves around data, while the fourth focuses on data wrangling. Part 5 teaches readers about exploring data. In Part 6 we learn to build models, Part 7 introduces the reader to the reality in companies, Part 8 covers reports and interactive applications and finally Part 9 introduces the reader to big data and performance computing. It also includes some helpful appendices. Provides a practical guide for non-experts with a focus on business users Contains a unique combination of topics including an introduction to R, machine learning, mathematical models, data wrangling, and reporting Uses a practical tone and integrates multiple topics in a coherent framework Demystifies the hype around machine learning and AI by enabling readers to understand the provided models and program them in R Shows readers how to visualize results in static and interactive reports Supplementary materials includes PDF slides based on the book’s content, as well as all the extracted R-code and is available to everyone on a Wiley Book Companion Site The Big R-Book is an excellent guide for science technology, engineering, or mathematics students who wish to make a successful transition from the academic world to the professional. It will also appeal to all young data scientists, quantitative analysts, and analytics professionals, as well as those who make mathematical models.