The R Student Companion

R is the amazing, free, open-access software package for scientific graphs and calculations used by scientists worldwide. The R Student Companion is a student-oriented manual describing how to use R in high school and college science and mathematics courses. Written for beginners in scientific computation, the book assumes the reader has just some

This book expertly guides the reader through all stages involved in undertaking quantitative psychological research, from accessing the relevant literature, through designing and conducting a study, analysing and interpreting data, and finally reporting the research. This third edition includes two new chapters - on preliminary checking of data and allowing for additional variables when comparing the means of different conditions - and expands on original topics such as choosing sample sizes and how to test for mediation effects. It also contains increased coverage of tests and further detail of techniques and terms which psychologists will meet when working with those in the medical professions. As the chapters focus on choosing appropriate statistical tests and how to interpret and report them (rather than the detailed calculations, which appear in appendices), the reader is able to gain an understanding of a test without being interrupted by the need to understand the complex mathematics behind it. In addition, for the first time, the book is accompanied by an online bank of multiple choice questions. The book helps readers to: Locate reports of relevant existing research Design research while adhering to ethical principles Identify various methods which can be used to ask questions or observe behaviour Choose appropriate samples Display and analyse findings numerically and graphically to test hypotheses Report psychological research in a variety of ways. As such, the book is suitable for psychology students and professionals at all levels, and is particularly useful to those working in Health and Clinical Psychology.

In the contemporary world it is clear that the need to study beyond Masters Level is increasing in importance for a wide range of practitioners in diverse professional settings. Students across the world are choosing doctorates not only to become career academics, but to go beyond the academic arena, in order to make a personal and educational, as well as an economic investment, in their workplace careers and their lives. However for many doctoral students, both full-time and part-time, navigating the literature and key issues surrounding doctoral research can often be a challenge. Bringing together contributions from key names in the international education arena, The Routledge Doctoral Student’s Companion is a comprehensive guide to the literature surrounding doctorates, bringing together questions, challenges and solutions normally scattered over a wide range of texts. Accessible and wide-ranging, it covers all doctoral students need to know about: what doctoral education means in contemporary practice forming an identity and knowledge as a doctoral student the big questions which run throughout doctoral practice becoming a researcher the skills needed to conduct research integrating oneself into a scholarly community. Offering an extensive and rounded guide to undertaking doctoral research in a single volume, this book is essential reading for all full-time and part-time doctoral students in education and related disciplines.

Project-Based R Companion to Introductory Statistics is envisioned as a companion to a traditional statistics or biostatistics textbook, with each chapter covering traditional topics such as descriptive statistics, regression, and hypothesis testing. However, unlike a traditional textbook, each chapter will present its material using a complete step-by-step analysis of a real publicly available dataset, with an emphasis on the practical skills of testing assumptions, data exploration, and forming conclusions. The chapters in the main body of the book include a worked example showing the R code used at each step followed by a multi-part project for students to complete. These projects, which could serve as alternatives to traditional discrete homework problems, will illustrate how to "put the pieces together" and conduct a complete start-to-finish data analysis using the R statistical software package. At the end of the book, there are several projects that require the use of multiple statistical techniques that could be used as a take-home final exam or final project for a class. Key features of the text: Organized in chapters focusing on the same topics found in typical introductory statistics textbooks (descriptive statistics, regression, two-way tables, hypothesis testing for means and proportions, etc.) so instructors can easily pair this supplementary material with course plans Includes student projects for each chapter which can be assigned as laboratory exercises or homework assignments to supplement traditional homework Features real-world datasets from scientific publications in the fields of history, pop culture, business, medicine, and forensics for students to analyze Allows students to gain experience working through a variety of statistical analyses from start to finish The book is written at the undergraduate level to be used in an introductory statistical methods course or subject-specific research methods course such as biostatistics or research methods for psychology or business analytics. Author After a 10-year career as a research biostatistician in the Department of Ophthalmology and Visual Sciences at the University of Wisconsin-Madison, Chelsea Myers teaches statistics and biostatistics at Rollins College and Valencia College in Central Florida. She has authored or co-authored more than 30 scientific papers and presentations and is the creator of the MCAT preparation website MCATMath.com.

This compact, accessibly written text prepares students for their experience of community-based learning. It is designed for students to read and reflect on independently or to foster discussion in class on their motivations and dispositions toward community engagement and service learning. It prepares students to work with diverse individuals, groups, and organizations that may be outside their prior experience. Faculty can use the book as a tool to deepen the educational experience of the course and enrich community engagement. This text is a guide to what's involved in community-engaged learning, from understanding the pervasiveness of social, economic and environmental problems, to learning about how individuals and organizations in communities work to overcome them. Students will discover through a process of reflection how service connects to personal development and the content of their courses, builds their ability to engage with people different from themselves, and develops new life skills, all in the context of working with communities to overcome systemic injustice. Critical questions woven into each chapter prompt students to reflect on ideas and perspectives about social justice, community development, and their role in fostering them. The book concludes with case studies of students who have experienced the transformative power of community-engaged learning. The stories illustrate common themes inherent in the student experience, including listening to understand, challenging stereotypes, learning the nature of their role, and seeing the world through a new lens. A special feature of this book is the embedded QR codes that provide access, as students read the text, to online resources, and original and public videos that explore particular themes or perspectives more deeply. The authors also include text directed to faculty to provide ideas about framing their community-engaged course and integrating the book.

An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, flexible, and free tool. However, the flexibility—which eventually becomes a great asset—can make the initial learning curve appear steep. This book introduces a few key aspects of the R tool. As readers become comfortable with these aspects, they develop a foundation from which to more thoroughly explore R and the packages available for it. This introduction does not explain every possible way to analyze data or perform a specific type of analysis. Rather, it focuses on the analyses that are traditionally included in an undergraduate statistics course and provides one or two ways to run these analyses in R. Datasets and scripts to run the examples are provided on an accompanying website. The book has been designed to be an R companion to Warner′s Applied Statistics I, Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide, without reference to the Warner text.

Social Policy and Welfare is an introductory textbook to the key concepts, issues and historical developments that underpin British social policy. The book includes coverage of both classic themes and debates and the latest New Labour approach to social policy and social welfare provision. Written with the Edexcel Social policy AS/A level specifications in mind, it should be of specific interest to undergraduates studying social policy, sociology, and to health and social care students.

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis. John Fox and Sanford Weisberg provide a step-by-step guide to using the free statistical software R, an emphasis on integrating statistical computing in R with the practice of data analysis, coverage of generalized linear models, and substantial web-based support materials. The Third Edition has been reorganized and includes a new chapter on mixed-effects models, new and updated data sets, and a de-emphasis on statistical programming, while retaining a general introduction to basic R programming. The authors have substantially updated both the car and effects packages for R for this edition, introducing additional capabilities and making the software more consistent and easier to use. They also advocate an everyday data-analysis workflow that encourages reproducible research. To this end, they provide coverage of RStudio, an interactive development environment for R that allows readers to organize and document their work in a simple and intuitive fashion, and then easily share their results with others. Also included is coverage of R Markdown, showing how to create documents that mix R commands with explanatory text. "An R Companion to Applied Regression continues to provide the most comprehensive and user-friendly guide to estimating, interpreting, and presenting results from regression models in R." –Christopher Hare, University of California, Davis

This is the second revised edition of A Student's Companion to Old Irish Grammar, which originally appeared in 2013. This book, written in an intentionally informal style, aims to make Old Irish grammar more accessible to students of all backgrounds. It can serve as a stand-alone introduction or can be used in conjunction with other grammatical works, in hopes of elucidating some of the tricky concepts that makes Old Irish such a fascinating and rewarding subject for study.

The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples. About the Author: Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

This historic book may have numerous typos and missing text. Purchasers can usually download a free scanned copy of the original book (without typos) from the publisher. Not indexed. Not illustrated. 1888 edition. Excerpt: ...apparel and sought and obtained employment as a teamster in the quartermasters department. Her features were very large, and so coarse and masculine was her general appearance that she would readily have passed as a man, and in her case the deception was no doubt easily practiced. Next day the "she dragoon " was caught, and proved to be a rather prepossessing young woman, and though necessarily bronzed and hardened by exposure, I doubt if, even with these marks of campaigning, she could have deceived as readily as did her companion. How the two got acquainted I never learned, and though they had joined the army independently of each other, yet an intimacy had sprung up between them long before the mishaps of the foraging expedition. They both were forwarded to army headquarters, and, when provided with clothing suited to their sex, sent back to Nashville, and thence beyond our lines to Louisville. On January 9, by an order from the War Department, the Army of the Cumberland had been divided into three corps, designated the Fourteenth, Twentieth, and Twenty-first. This order did not alter the composition of the former grand divisions, nor change the commanders, but the new nomenclature was a decided improvement over the clumsy designations Right Wing, Centre, and Left Wing, which were well calculated to lead to confusion sometimes. McCooks wing became the Twentieth Corps, and my division continued of the same organization, and held the same number as formerly--the Third Division, Twentieth Corps. My first brigade was now commanded by Brigadier-General William H. Lytle, the second by Colonel Bernard Laiboldt, and the third by Colonel Luther P. Bradley. On the 4th of March I was directed to move in light marching order toward Franklin and...

This popular book incorporates modern approaches to physics. It not only tells readers how physics works, it shows them. Applications have been enhanced to form a bridge between concepts and reasoning.

The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.

This essential guide to studying geography has been updated to ensure it remains a valuable resource for all those on geography courses, as well as those considering studying the subject at university. Second edition of this popular and wide-ranging guide to studying geography. Includes contributions from many key geographers around the world. Provides answers to questions from before starting a degree course right through to further study and careers. Includes lots of practical tips for improving geographical study and research skills. Fully revised and updated to ensure it remains an invaluable resource for students.

Designed for undergraduate students, A Mathematics Companion for Science and Engineering Students provides a valuable reference for a wide variety of topics in precalculus mathematics. The presentation is precise, accurate, and complete, with helpful comments throughout.

The Student's Companion to Physiotherapy is a comprehensive guide to help ease the stresses and strains of studying physiotherapy. It puts a lighter spin on a very challenging time but is very informative, identifying the vital facts in anatomy and physiology; neurological physiotherapy; electrotherapy; respiratory physiotherapy; musculoskeletal physiotherapy; pharmacology; bio-psychosocial approach; paediatrics; portfolio development; and methods of work/assessment. The content here is orchestrated by students wanting to share their knowledge with fellow students and this book will be a trusty companion for all budding physiotherapists. Offers students unique learning and study skills needed for physiotherapy Specifies useful ways to study and offers advice on portfolio development and communication as a clinician Anecdotes, "top tips" boxes and cartoons Handy hints on portfolio development, research and job applications

An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to analyze multivariate data. The book focuses on the statistics generally covered in an intermediate or multivariate statistics course and provides one or two ways to run each analysis in R. The book has been designed to be an R companion to Rebecca M. Warner′s Applied Statistics II: Third Edition, and includes end-of-chapter instructions for replicating the examples from that book in R. However, this text can also be used as a stand-alone R guide for a multivariate statistics course, without reference to the Warner text. Datasets and scripts to run the examples are provided on an accompanying website.

Quantitative Psychological Research: The Complete Student's Companion expertly guides the reader through all the stages involved in undertaking quantitative psychological research: designing a study, choosing a sample of people, undertaking the study, analysing the data, and reporting the research. Accessibly written and clearly presented, the book is designed for anyone learning to conduct quantitative psychological research. It covers the full research process, from the original idea to reporting the completed study, emphasising the importance of looking beyond statistical significance in evaluating data. The book provides step-by-step guidance on choosing, interpreting and reporting the appropriate analysis, featuring worked examples and extended calculations as appendices for advanced readers. This edition features new chapters on exploratory factor analysis, logistic regression and Bayesian statistics, and has been thoroughly updated throughout to reflect the latest research practices. Care has been taken to avoid tying the book to any specific statistical software, providing readers with a thorough grounding in the basics no matter which package they go on to use. Whether you’re at the beginning of your undergraduate degree or working towards your masters or doctorate, this book will be invaluable for anyone looking to understand how to conduct quantitative psychological research.

Are you a researcher or instructor who has been wanting to learn R and RStudio®, but you don′t know where to begin? Do you want to be able to perform all the same functions you use in IBM® SPSS® in R? Is your license to IBM® SPSS® expiring, or are you looking to provide your students guidance to a freely-available statistical software program? Moving from IBM® SPSS® to R and RStudio®: A Statistics Companion is a concise and easy-to-read guide for users who want to know learn how to perform statistical calculations in R. Brief chapters start with a step-by-step introduction to R and RStudio, offering basic installation information and a summary of the differences. Subsequent chapters walk through differences between SPSS and R, in terms of data files, concepts, and structure. Detailed examples provide walk-throughs for different types of data conversions and transformations and their equivalent in R. Helpful and comprehensive appendices provide tables of each statistical transformation in R with its equivalent in SPSS and show what, if any, differences in assumptions factor to into each function. Statistical tests from t-tests to ANOVA through three-factor ANOVA and multiple regression and chi-square are covered in detail, showing each step in the process for both programs. By focusing just on R and eschewing detailed conversations about statistics, this brief guide gives adept SPSS® users just the information they need to transition their data analyses from SPSS to R.