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Learning Statistics Using R
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Learning Statistics Using R

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January 2014 | 648 pages | SAGE Publications, Inc

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. 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.

Available with Perusall—an eBook that makes it easier to prepare for class
Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more


 
PART I. Introduction and Background
 
1. R Basics
 
2. Research Methods
 
3. Probability
 
4. Sampling and Populations
 
PART II. Statistical Theory and Inference
 
5. Central Limit Theorem
 
6. Sampling Distributions
 
7. Statistical Distributions
 
PART III. Descriptive Methods
 
8. Graphing Data
 
9. Central Tendency and Dispersion
 
PART IV. Statistical Methods
 
10. Hypothesis Testing
 
11. Chi-Square Test for Categorical Data
 
12. z Test for Differences in Proportions
 
13. t Test for Mean Differences (2 groups)
 
14. F Test for Mean Differences (3 or more groups)
 
15. Correlation Tests of Association
 
16. Linear Regression Tests of Prediction
 
17. Multiple Regression
 
18. Logistic Regression
 
19. Loglinear Regression
 
PART V. Replication and Validation of Research Findings
 
20. Replication of Statistical Tests
 
21. Synthesis of Research Findings
 
Glossary of Terms
 
Glossary of Packages, Functions, and Commands Used in Book
 
Statistical Tables
 
Guide for Selecting a Statistical Test

Supplements

Instructor Resource Site

Calling all instructors!
It’s easy to log on to SAGE’s password-protected Instructor Teaching Site at www.sagepub.com/schumacker for complete and protected access to all text-specific Instructor Resources for Learning Statistics Using R. Simply provide your institutional information for verification and within 72 hours you’ll be able to use your login information for any SAGE title!

Password-protected Instructor Resources include the following:

  • A Microsoft® Word® test bank is available containing multiple choice, true/false, short answer, and essay questions for each chapter. The test bank provides you with a diverse range of pre-written options as well as the opportunity for editing any question and/or inserting your own personalized questions to effectively assess students’ progress and understanding.
  • A Respondus electronic test bank is available and can be used on PCs. The test bank contains multiple choice, true/false, short answer, and essay questions for each chapter and provides you with a diverse range of pre-written options as well as the opportunity for editing any question and/or inserting your own personalized questions to effectively assess students’ progress and understanding. Respondus is also compatible with many popular learning management systems so you can easily get your test questions into your online course.
  • Editable, chapter-specific Microsoft® PowerPoint® slides offer you complete flexibility in easily creating a multimedia presentation for your course. Highlight essential content, features, and artwork from the book.
  • The Instructor Teaching Site includes complete answers to all in-text questions.
  • Data sets are available for practice exercises.
  • EXCLUSIVE! Access to certain full-text SAGE journal articles that have been carefully selected for each chapter. Each article supports and expands on the concepts presented in the chapter. This feature also provides questions to focus and guide student interpretation. Combine cutting-edge academic journal scholarship with the topics in your course for a robust classroom experience.
  • Lecture notes summarize key concepts on a chapter-by-chapter basis to help with preparation for lectures and class discussions.
Student Study Site
Use the Student Study Site to get the most out of your course!

The open-access Student Study Site at www.sagepub.com/schumacker includes the following:

  • Mobile-friendly eFlashcards reinforce understanding of key terms and concepts that have been outlined in the chapters.
  • Mobile-friendly web quizzes allow for independent assessment of progress made in learning course material.

A well thought out text that explains fundamental statistics well - this is a text that aims to support statistics courses, it is not a manual for R. But it does use R well to illustrate statistical approaches and users will gain a good knowledge of R while using the text.

Dr Ivan Gee
Fac of Health & Applied Social Scienc, Liverpool John Moores University
October 14, 2015

The book does exactly what it says on its cover. Although R language may seem difficult to handle at the beginning, the structure and the abundance of examples and reinforcements notes contained in the book would make it a first reading choice.

Dr Tim Constantin
Health , Nottingham University
May 7, 2015

R seems exceptionally complicated for introductory statistics students. I am considering adopting this book for an advanced quantitative methods class that I will be teaching in subsequent semesters.

Dr Jon Maskaly
Criminal Justice Dept, University Of Illinois-Chicago
April 5, 2015

Students find that learning R is too demanding at this point in their career.

Dr David Rothwell
Social Work, McGill Univ
December 10, 2014

The book is pretty detailed when it comes to statistical concepts and tests. It is therefore not only useful in teaching/learning the handling of R, but helps with understand statistical concepts.

Mrs Claudia Seifert
Communication, Technical University of Dresden
September 3, 2014

Seems adequate for introductory statistics. Good introduction to R. Access to the R scripts should be very helpful.

Mr Mark Van Ryzin
educational methodology, policy, and leadership, University Of Oregon
July 27, 2014

Good text in all ramnification.

Dr Olatunde Aremu
School of Health and Bioscience, Univ. of East London
July 20, 2014

A very interesting text

Dr Antonio Oller-Marcen
Matemáticas, estadística e I.O., Centro Universitario de la Defensa
June 27, 2014

A clear book on an alternative way of analysing data. Too advanced for this purpose, but perhaps of interest to advanced students.

Miss Rebecca Wheeler
Department of Psychology, Coventry University
June 10, 2014

committee decision

Dr Bal Barot
Science, Lake Michigan Clg-Napier Ave
May 22, 2014
Key features

KEY FEATURES:

  • The book follows the logic of data input from vectors, arrays, matrices, and data frames to the input of data sets from SPSS, SAS, STATA, and other software packages.
  • The book describes the processing of variables used in statistical procedures and shows output from the R functions, as well as customized tables and graphs.
  • Learning to use R gives readers the freedom to use it in learning and conducting statistical analyses on different computer operating systems without the expense of commercial software.
  • R software is free, easy-to-use, portable and can be used on Apple, PC, and Linux computer operating systems.

Sample Materials & Chapters

Chapter 5

Chapter 16


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