Beginning R: An Introduction to Statistical Programming (Expert's Voice in Programming)

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Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics.

R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.

  • Covers the freely-available R language for statistics
  • Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more
  • Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done

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From the Author:

This book is being revised and will be in a second edition in 2015. I am completely rewriting the book to include more current information and many more applications than the first edition covered.

About the Author:

Dr. Larry Pace is a statistics author and educator, as well as a consultant. He lives in the upstate area of South Carolina in the town of Anderson. He is a professor of statistics, mathematics, psychology, management, and leadership. He has programmed in a variety of languages and scripting languages including R, Visual Basic, JavaScript, C##, PHP, APL, and in a long-ago world, Fortran IV. He writes books and tutorials on statistics, computers, and technology. He has also published many academic papers, and made dozens of presentations and lectures. He has consulted with Compaq Computers, AT&T, Xerox Corporation, the U.S. Navy, and International Paper. He has taught at Keiser University, Argosy University, Capella University, Ashford University, Anderson University (where he was the chair of the behavioral sciences department), Clemson University, Louisiana Tech University, LSU in Shreveport, the University of Tennessee, Cornell University, Rochester Institute of Technology, Rensselaer Polytechnic Institute, and the University of Georgia.

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Book Description Springer-Verlag Berlin and Heidelberg GmbH Co. KG, Germany, 2012. Paperback. Condition: New. 1st ed.. Language: English . Brand New Book. Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by ATT. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done. Seller Inventory # KNV9781430245544

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Book Description Springer-Verlag Berlin and Heidelberg GmbH Co. KG, Germany, 2012. Paperback. Condition: New. 1st ed.. Language: English . Brand New Book. Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by ATT. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done. Seller Inventory # KNV9781430245544

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Book Description Condition: New. Publisher/Verlag: Springer, Berlin | An Introduction to Statistical Programming | Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics.R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done | Part I. Learning the R Language1. Getting R and Getting Started2. Programming in R3. Writing Reusable Functions4. Summary StatisticsPart II. Using R for Descriptive Statistics5. Creating Tables and Graphs6. Discrete Probability Distributions7. Computing Standard Normal ProbabilitiesPart III. Using R for Inferential Statistics8. Creating Confidence Intervals9. Performing t Tests10. Implementing One-Way ANOVA11. Implementing Advanced ANOVA12. Simple Correlation and Regression in R13. Multiple Correlation and Regression in R14. Logistic Regression15. Performing Chi-Square Tests16. Working in Nonparametric StatisticsPart IV. Taking R to the Next Level17. Using R for Simulation18. Resampling and Bootstrapping19. Creating R Packages20. Executing R Packages | Format: Paperback | Language/Sprache: english | 581 gr | 237x192x18 mm | 336 pp. Seller Inventory # K9781430245544

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Book Description APress. Paperback. Condition: New. 336 pages. Dimensions: 9.2in. x 7.4in. x 0.8in.Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT and T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done What youll learn Acquire and install R Import and export data and scripts Generate basic statistics and graphics Program in R to write custom functions Use R for interactive statistical explorations Implement simulations and other advanced techniques Who this book is for Beginning R: An Introduction to Statistical Programming is an easy-to-read book that serves as an instruction manual and reference for working professionals, professors, and students who want to learn and use R for basic statistics. It is the perfect book for anyone needing a free, capable, and powerful tool for exploring statistics and automating their use. Table of ContentsPart I. Learning the R Language 1. Getting R and Getting Started 2. Programming in R 3. Writing Reusable Functions 4. Summary Statistics Part II. Using R for Descriptive Statistics 5. Creating Tables and Graphs 6. Discrete Probability Distributions 7. Computing Standard Normal Probabilities Part III. Using R for Inferential Statistics 8. Creating Confidence Intervals 9. Performing t Tests 10. Implementing One-Way ANOVA 11. Implementing Advanced ANOVA 12. Simple Correlation and Regression in R 13. Multiple Correlation and Regression in R 14. Logistic Regression 15. Performing Chi-Square Tests 16. Working in Nonparametric Statistics Part IV. Taking R to the Next Level 17. Using R for Simulation 18. Resampling and Bootstrapping 19. Creating R Packages 20. Executing R Packages This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Seller Inventory # 9781430245544

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