Understanding Statistics Using R
Autor Randall Schumacker, Sara Tomeken Limba Engleză Hardback – 24 ian 2013
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.
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| Springer – 8 feb 2015 | 517.47 lei 6-8 săpt. | |
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| Springer – 24 ian 2013 | 632.73 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781461462262
ISBN-10: 1461462266
Pagini: 292
Ilustrații: XVI, 292 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.57 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
ISBN-10: 1461462266
Pagini: 292
Ilustrații: XVI, 292 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.57 kg
Ediția:2013
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
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Public țintă
Upper undergraduateCuprins
R Fundamentals.- Probability.- Statistical Theory.- Frequency Distributions.- Central Tendency and Dispersion.- Statistical Distributions.- Hypothesis Testing.- Chi-Square Test.- z-test.- t-test.- F-test.- Correlation.- Linear Regression.- Replication of Results.- Synthesis of Findings.- Glossary.- Appendix.- Author Index.- Subject Index.
Recenzii
From the reviews:
“The code is arranged by chapter. It is easy and straight forward to run the code. The chapters have lots of exercises. This is a good book to learn both statistics and R.” (Cats and Dogs with Data, maryannedata.com, March, 2014)
“This book is organized in a methodical manner. … each chapter ends with a sample output so readers can check their own R code and true/false questions to test readers’ knowledge. … this is a well-done book that will be useful for self-learners or specialists in application areas who can use it as a practical source for statistical analysis, as well as the source of R code for libraries.” (Mike Minkoff, Computing Reviews, August, 2013)
"The monograph presents an introductory course on statistics, with numerous illustrations using R. In its 15 chapters, the book covers such topics as R installation, laws of probability, randomness, distributions of various kinds, hypothesis testing, classical Chi-square, z-, t-,and F-tests, correlation and linear regression, resamplingwith jackknife, bootstrap, and cross validation, andmetaanalysis and significance...those who already are familiar with R can find the book useful for an introduction to statistical concepts, with the numerical examples which can be reproduced by the downloaded scripts."
Technometrics 56:1 2014
“The code is arranged by chapter. It is easy and straight forward to run the code. The chapters have lots of exercises. This is a good book to learn both statistics and R.” (Cats and Dogs with Data, maryannedata.com, March, 2014)
“This book is organized in a methodical manner. … each chapter ends with a sample output so readers can check their own R code and true/false questions to test readers’ knowledge. … this is a well-done book that will be useful for self-learners or specialists in application areas who can use it as a practical source for statistical analysis, as well as the source of R code for libraries.” (Mike Minkoff, Computing Reviews, August, 2013)
"The monograph presents an introductory course on statistics, with numerous illustrations using R. In its 15 chapters, the book covers such topics as R installation, laws of probability, randomness, distributions of various kinds, hypothesis testing, classical Chi-square, z-, t-,and F-tests, correlation and linear regression, resamplingwith jackknife, bootstrap, and cross validation, andmetaanalysis and significance...those who already are familiar with R can find the book useful for an introduction to statistical concepts, with the numerical examples which can be reproduced by the downloaded scripts."
Technometrics 56:1 2014
Notă biografică
Randall E. Schumacker is Professor of Educational Research in the Department of Educational Studies in Psychology, Research Methodology & Counseling at the University of Alabama, USA.
Sara Tomek is Assistant Professor of Educational Research in the Department of Educational Studies in Psychology, Research Methodology & Counseling at the University of Alabama, USA.
Sara Tomek is Assistant Professor of Educational Research in the Department of Educational Studies in Psychology, Research Methodology & Counseling at the University of Alabama, USA.
Textul de pe ultima copertă
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.
This book uses the R statistical package which contains an extensive library of functions. The R software is free and easily downloaded and installed. The R programs are run in the R Studio software which is a graphical user interface for Windows. The R Studio software makes accessing R programs, viewing output from the exercises, and graphical displays easier to manage. The first chapter of the book covers the fundamentals of the R statistical package. This includes installation of R and R Studio, accessing R packages and libraries of functions. The chapter also covers how to access manuals and technical documentation, as well as, basic R commands used in the R script programs in the chapters. This chapter is important for the instructor to master so that the software can be installed and the R script programs run. The R software is free so students can also install the software and run the R script programs in the chapters. Teachers and students can run the R software on university computers, at home, or on laptop computers making it more available than many commercial software packages.
"As a professor who teaches research methods and advises master and doctoral students, I am often seeking practical resource materials that students can use in their research. This book provides easy to run R examples that allow students to pick and choose content that is relevant to their research. When students learn that the cost for running R is free, they are especially happy!"
- Kim Nimon, University of North Texas
"The authors have done a great job of providing resource materials an instructor can use when teaching a statistics course. Strengths of the book are the inclusion of R code, the addition of more than 60 script programs, and the online exercise materials for students. This book reflects the growing use of the mobile R software program for students who may not always have access to other statistical software packages housed on computers in a campus-based lab."
- David Walker, Northern Illinois University
This book uses the R statistical package which contains an extensive library of functions. The R software is free and easily downloaded and installed. The R programs are run in the R Studio software which is a graphical user interface for Windows. The R Studio software makes accessing R programs, viewing output from the exercises, and graphical displays easier to manage. The first chapter of the book covers the fundamentals of the R statistical package. This includes installation of R and R Studio, accessing R packages and libraries of functions. The chapter also covers how to access manuals and technical documentation, as well as, basic R commands used in the R script programs in the chapters. This chapter is important for the instructor to master so that the software can be installed and the R script programs run. The R software is free so students can also install the software and run the R script programs in the chapters. Teachers and students can run the R software on university computers, at home, or on laptop computers making it more available than many commercial software packages.
"As a professor who teaches research methods and advises master and doctoral students, I am often seeking practical resource materials that students can use in their research. This book provides easy to run R examples that allow students to pick and choose content that is relevant to their research. When students learn that the cost for running R is free, they are especially happy!"
- Kim Nimon, University of North Texas
"The authors have done a great job of providing resource materials an instructor can use when teaching a statistics course. Strengths of the book are the inclusion of R code, the addition of more than 60 script programs, and the online exercise materials for students. This book reflects the growing use of the mobile R software program for students who may not always have access to other statistical software packages housed on computers in a campus-based lab."
- David Walker, Northern Illinois University
Caracteristici
Provides strong fundamental Background in statistics and probability through simulation exercises Perfect resource for advanced undergraduates and professionals. Anyone who has at least taken one course with experience/knowledge in linear regression R software code utilized throughout for assessment and interpretation of data and data mining exercises ? Includes supplementary material: sn.pub/extras Request lecturer material: sn.pub/lecturer-material