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Moving from IBM® SPSS® to R and RStudio®

Author : Howard T. Tokunaga

Publisher : SAGE Publications, Incorporated

Page : 313 pages

File Size : 28,44 MB

Release : 2021-02-02

Category : Psychology

ISBN : 1071817043

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Book Description

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.



Moving from IBM® SPSS® to R and RStudio®

Author : Howard T. Tokunaga

Publisher : SAGE Publications

Page : 551 pages

File Size : 12,23 MB

Release : 2021-02-12

Category : Psychology

ISBN : 1071817019

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Book Description

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.



Introduction to R in IBM SPSS Modeler

Author : Wannes Rosius

Publisher : IBM Redbooks

Page : 54 pages

File Size : 43,64 MB

Release : 2016-10-14

Category : Computers

ISBN : 0738455601

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Book Description

This IBM RedpaperTM publication focuses on the integration between IBM® SPSS® Modeler and R. The paper is aimed at people who know IBM SPSS Modeler and have only a very limited knowledge of R. Chapters 2, 3, and 4 provide you with a high level understanding of R integration within SPSS Modeler enabling you to create or recreate some very basic R models within SPSS Modeler, even if you have only a basic knowledge of R. Chapter 5 provides more detailed tips and tricks. This chapter is for the experienced user and consists of items that might help you get up to speed with more detailed functions of the integration and understand some pitfalls.



A Guide to R for Social and Behavioral Science Statistics

Author : Brian Joseph Gillespie

Publisher : SAGE Publications

Page : 268 pages

File Size : 20,5 MB

Release : 2020-02-07

Category : Social Science

ISBN : 1544344007

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Book Description

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate students, shown in the R statistical language using RStudio®. The book is geared toward social and behavioral science statistics students, especially those with no background in computer science. Written as a companion book to be used alongside a larger introductory statistics text, the text follows the most common progression of statistics for social scientists. The guide also serves as a companion for conducting data analysis in a research methods course or as a stand-alone R and statistics text. This guide can teach anyone how to use R to analyze data, and uses frequent reminders of basic statistical concepts to accompany instructions in R to help walk students through the basics of learning how to use R for statistics.



Multilevel Modeling

Author : G. David Garson

Publisher : SAGE Publications

Page : 553 pages

File Size : 21,30 MB

Release : 2019-07-31

Category : Education

ISBN : 1544319304

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Book Description

Providing a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences.



Transforming Healthcare with Big Data and AI

Author : Alex Liu

Publisher : IAP

Page : 184 pages

File Size : 38,33 MB

Release : 2020-04-01

Category : Computers

ISBN : 1641138998

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Book Description

Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.



Data Science for Business With R

Author : Jeffrey S. Saltz

Publisher : SAGE Publications, Incorporated

Page : 423 pages

File Size : 42,96 MB

Release : 2021-02-03

Category : Business & Economics

ISBN : 1544370482

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Book Description

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.



A Practical Introduction to Real-World Research

Author : Loreen Wolfer

Publisher : SAGE Publications

Page : 466 pages

File Size : 48,33 MB

Release : 2021-01-15

Category : Social Science

ISBN : 1544378289

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Book Description

This practical text combines social research methods with coverage of statistical analysis to help students develop the applied research skills needed for future careers in public and private organizations, while also delivering a solid foundation for those going on to graduate school. Throughout the book, the author offers a real-world example and then breaks it down into a decision tree, which helps lead students to a possible statistical decision (rather than starting with the statistic). This text gives students a toolbox of the most common and in-demand skills and demonstrates how those skills can be used to make the best research decisions. The book takes students through the entire real-world research process, from the formation of a research topic to measurement and sampling, to methods for gathering information and making sense of the data, and finally presenting to a non-academic audience in a way that "gets the job done." Resources for instructors and students are available on an accompanying website for the book.



Using R With Multivariate Statistics

Author : Randall E. Schumacker

Publisher : SAGE Publications

Page : 409 pages

File Size : 44,7 MB

Release : 2015-06-18

Category : Social Science

ISBN : 1483377954

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Book Description

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.



R for Cloud Computing

Author : A Ohri

Publisher : Springer

Page : 281 pages

File Size : 22,78 MB

Release : 2014-11-14

Category : Computers

ISBN : 1493917021

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Book Description

R for Cloud Computing looks at some of the tasks performed by business analysts on the desktop (PC era) and helps the user navigate the wealth of information in R and its 4000 packages as well as transition the same analytics using the cloud. With this information the reader can select both cloud vendors and the sometimes confusing cloud ecosystem as well as the R packages that can help process the analytical tasks with minimum effort, cost and maximum usefulness and customization. The use of Graphical User Interfaces (GUI) and Step by Step screenshot tutorials is emphasized in this book to lessen the famous learning curve in learning R and some of the needless confusion created in cloud computing that hinders its widespread adoption. This will help you kick-start analytics on the cloud including chapters on both cloud computing, R, common tasks performed in analytics including the current focus and scrutiny of Big Data Analytics, setting up and navigating cloud providers. Readers are exposed to a breadth of cloud computing choices and analytics topics without being buried in needless depth. The included references and links allow the reader to pursue business analytics on the cloud easily. It is aimed at practical analytics and is easy to transition from existing analytical set up to the cloud on an open source system based primarily on R. This book is aimed at industry practitioners with basic programming skills and students who want to enter analytics as a profession. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. It will also help researchers and academics but at a practical rather than conceptual level. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The cloud computing paradigm is firmly established as the next generation of computing from microprocessors to desktop PCs to cloud.