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Understanding Statistics Using R by Randall Schumacker and Sara Tomek (2013, Hardcover)
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About this product
Product Identifiers
PublisherSpringer New York
ISBN-101461462266
ISBN-139781461462262
eBay Product ID (ePID)143724551
Product Key Features
Number of PagesXvi, 292 Pages
Publication NameUnderstanding Statistics Using R
LanguageEnglish
SubjectMathematical & Statistical Software, Computer Simulation, Probability & Statistics / General, Computer Science, Statistics
Publication Year2013
TypeTextbook
AuthorRandall Schumacker, Sara Tomek
Subject AreaMathematics, Computers, Social Science
FormatHardcover
Dimensions
Item Weight206.6 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
Dewey Edition23
ReviewsFrom 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, From the reviews: "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, 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
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal519.502855133
Table Of ContentR 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.
SynopsisThis 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 provides a strong fundamental background in statistics and probability through simulation exercises. R software code is utilized throughout for assessment and interpretation of data and data mining exercises.
LC Classification NumberQA276.4-.45
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