Learning Statistics Using R

This includes the RStudio software, which is a Windows graphical user interface that makes navigating and using R easier ... Chapters 5 to 7 are therefore central to understanding statistics and the family of distributions for different ...

Author: Randall E. Schumacker

Publisher: SAGE Publications

ISBN: 9781483324777

Category: Social Science

Page: 648

View: 444

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Providing easy-to-use R script programs that teach descriptive statistics, graphing, and other statistical methods, Learning Statistics Using R shows readers how to run and utilize R, a free integrated statistical suite that has an extensive library of functions. Lecturers - contact your local SAGE representative to discuss your course needs or to request an inspection copy. Randall E. Schumacker’s comprehensive book describes in detail the processing of variables in statistical procedures. Covering a wide range of topics, from probability and sampling distribution to statistical theorems and chi-square, this introductory book helps readers learn not only how to use formulae to calculate statistics, but also how specific statistics fit into the overall research process. Learning Statistics Using R covers data input from vectors, arrays, matrices and data frames, as well as the input of data sets from SPSS, SAS, STATA and other software packages. Schumacker’s text provides the freedom to effectively calculate, manipulate, and graphically display data, using R, on different computer operating systems without the expense of commercial software. Learning Statistics Using R places statistics within the framework of conducting research, where statistical research hypotheses can be directly addressed. Each chapter includes discussion and explanations, tables and graphs, and R functions and outputs to enrich readers′ understanding of statistics through statistical computing and modeling.

Learning Statistics with R

And if you don't already know how to program, then learning how to do statistics using R is a nice way to start. Those are the main reasons I use R. It's not without its flaws: it's not easy to learn ...

Author: Daniel Navarro

Publisher: Lulu.com

ISBN: 9781326189723

Category:

Page:

View: 176

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Statistics for People Who Think They Hate Statistics Using R

In working on this R edition, we were trying to keep the informal tone, easy-to-follow examples, and useful figures and tables for learning statistics while introducing R as a useful, free tool to support that endeavor.

Author: Neil J. Salkind

Publisher: SAGE Publications

ISBN: 9781544324555

Category: Social Science

Page: 536

View: 224

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Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS® and Excel® versions are joined by a text for use with the R software, Statistics for People Who (Think They) Hate Statistics Using R. New co-author Leslie A. Shaw carries forward Salkind’s signature humorous, personable, and informative approach as the text guides students in a grounding of statistical basics and R computing, and the application of statistics to research studies. The book covers various basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more. A Complete Teaching & Learning Package SAGE Premium Video SAGE Premium Video tools and resources boost comprehension and bolster analysis. Videos include screencast tutorials that demonstrate setting up data and running selected problems in R. Learn more. SAGE edge FREE online resources for students that make learning easier. See how your students benefit.

Using R With Multivariate Statistics

... Understanding Statistical Concepts Using S-PLUS, Understanding Statistics Using R, and Learning Statistics Using R. He was the founder and is now Emeritus Editor of Structural Equation Modeling: A Multidisciplinary Journal, ...

Author: Randall E. Schumacker

Publisher: SAGE Publications

ISBN: 9781483377957

Category: Social Science

Page: 408

View: 526

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Using R with Multivariate Statistics by Randall E. Schumacker is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.

Data Science in Education Using R

Statistics Introductory statistics Open Intro. (2019). Textbooks. https://www.openintro.org/ Three open-source textbooks for statistics, one for high school students. Navarro, D. (2019). Learning statistics with R.

Author: Ryan A. Estrellado

Publisher: Routledge

ISBN: 9781000200904

Category: Education

Page: 284

View: 885

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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.

Learning Statistics with R

After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics ARE covered at the end of the book.

Author: Daniel Joseph Navarro

Publisher:

ISBN: OCLC:1048253860

Category: Statistics

Page:

View: 374

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Learning Statistics with R covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software. The book discusses how to get started in R as well as giving an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics ARE covered at the end of the book.

An Introduction to Statistical Learning

This book presents some of the most important modeling and prediction techniques, along with relevant applications.

Author: Gareth James

Publisher: Springer Nature

ISBN: 9781071614181

Category: Mathematics

Page: 607

View: 665

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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 to marketing to 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. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

The R Software

The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced.

Author: Pierre Lafaye de Micheaux

Publisher: Springer

ISBN: 1461490197

Category: Computers

Page: 628

View: 998

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The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Using R for Introductory Statistics

The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach.

Author: John Verzani

Publisher: CRC Press

ISBN: 9781315360300

Category: Mathematics

Page: 518

View: 765

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The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

An Adventure in Statistics

Socratic dialogue in the story helps students understand the basics behind even the more complex statistical concepts, reinforcing critical thinking and problem-solving skills.

Author: Andy Field

Publisher: Sage Publications Limited

ISBN: 1446210448

Category: Statistics

Page: 768

View: 290

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Shortlisted for the British Book Design and Production Awards 2016 Shortlisted for the Association of Learned & Professional Society Publishers Award for Innovation in Publishing 2016 An Adventure in Statistics: The Reality Enigma by best-selling author and award-winning teacher Andy Field offers a better way to learn statistics. It combines rock-solid statistics coverage with compelling visual story-telling to address the conceptual difficulties that students learning statistics for the first time often encounter in introductory courses - guiding students away from rote memorization and toward critical thinking and problem solving. Field masterfully weaves in a unique, action-packed story starring Zach, a character who thinks like a student, processing information, and the challenges of understanding it, in the same way a statistics novice would. Illustrated with stunning graphic novel-style art and featuring Socratic dialogue, the story captivates readers as it introduces them to concepts, eliminating potential statistics anxiety. The book assumes no previous statistics knowledge nor does it require the use of data analysis software. It covers the material you would expect for an introductory level statistics course that Field''s other books (Discovering Statistics Using IBM SPSS Statistics and Discovering Statistics Using R) only touch on, but with a contemporary twist, laying down strong foundations for understanding classical and Bayesian approaches to data analysis. In doing so, it provides an unrivalled launch pad to further study, research, and inquisitiveness about the real world, equipping students with the skills to succeed in their chosen degree and which they can go on to apply in the workplace. The Story and Main Characters The Reality Revolution In the City of Elpis, in the year 2100, there has been a reality revolution. Prior to the revolution, Elpis citizens were unable to see their flaws and limitations, believing themselves talented and special. This led to a self-absorbed society in which hard work and the collective good were undervalued and eroded. To combat this, Professor Milton Grey invented the reality prism, a hat that allowed its wearers to see themselves as they really were - flaws and all. Faced with the truth, Elpis citizens revolted and destroyed and banned all reality prisms. The Mysterious Disappearance Zach and Alice are born soon after all the prisms have been destroyed. Zach, a musician who doesn''t understand science, and Alice, a geneticist who is also a whiz at statistics, are in love. One night, after making a world-changing discovery, Alice suddenly disappears, leaving behind a song playing on a loop and a file with her research on it. Statistics to the Rescue! Sensing that she might be in danger, Zach follows the clues to find her, as he realizes that the key to discovering why Alice has vanished is in her research. Alas! He must learn statistics and apply what he learns in order to overcome a number of deadly challenges and find the love of his life. As Zach and his pocket watch, The Head, embark on their quest to find Alice, they meet Professor Milton Grey and attractive Celia, battle zombies, cross a probability bridge, and encounter Jig:Saw, a mysterious corporation that might have something to do with Alice''s disappearance... Author News "Eight years ago I had the idea to write a fictional story through which the student learns statistics via a shared adventure with the main character..." Read the complete article from Andy Field on writing his new book Times Higher Education article: "Andy Field takes statistics adventure to a new level" Stay Connected Connect with us on Facebook and share your experiences with Andy''s texts, check out news, access free stuff, see photos, watch videos, learn about competitions, and much more. Video Links Go behind the scenes and learn more about the man behind the book: Watch Andy talk about why he created a statistics book using the framework of a novel and illustrations by one of the illustrators for the show, Doctor Who. See more videos on Andy''s YouTube channel