Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley
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Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley
PDF Ebook Online Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3.
R is a powerful open-source language and programming environment for statistics 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, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. 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 data analysis and research.
What You Will Learn:
- How to acquire and install R
- Hot to import and export data and scripts
- How to analyze data and generate graphics
- How to program in R to write custom functions
- Hot to use R for interactive statistical explorations
- How to conduct bootstrapping and other advanced techniques
Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley - Amazon Sales Rank: #928461 in Books
- Published on: 2015-10-13
- Released on: 2015-10-13
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x .81" w x 7.00" l, .0 pounds
- Binding: Paperback
- 327 pages
Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley 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.
Where to Download Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley
Most helpful customer reviews
14 of 17 people found the following review helpful. Disappointing By William Venables I am not a beginner with R, but I am interested to see how people approach teaching R to beginners. It's not an easy system to approach, though it should be.Some beginners seem to like this book, which depresses me a bit. The code tends to be clumsy, and all too often just plain wrong. (Clearly no reproducibility mechanism has been used as some examples are even syntactically incorrect.) A certain amount of clumsiness is probably a good idea if it leads the beginner to an understanding by a more accessible route, but most of the clumsiness here does not. An example is where the author uses an awkward loop to produce a copy of the vector x omitting the ith component, when all that is needed is x[-i], and I cannot believe this is difficult, even for beginners.What disappoints me about this book is that all to often it makes life difficult for the user and heads off in, to put it mildly, unhelpful and confusing directions.The book has a technical reviewer as part of the authorship team, but the role seem more of an adviser than of a reviewer. In places the 'reviewer's' advice is acknowledged, but not actually adopted. This I find very puzzling.
2 of 3 people found the following review helpful. Great book for learning R By stock4166 I like this book because it takes a practical hands-on approach to learning R by walking one through practical examples. I think the book is appropriately titled. It's not an exhaustive reference manual or cookbook nor does it teach one statistics. I have a lot of experience with SAS and it was easy for me to learn R from this book using SAS as my frame of reference. Neither R nor SAS are Excel. The former are statistical languages and they assume that you are already comfortable with statistical methods.That said, it does have detailed examples on how to set up and run many of the popular statistical methods which I won't enumerate here because you can read them all in the table of contents. Each section of the book that discusses a particular statistical method begins with an overview the relevant equations supporting it. I like the examples of plotting results. I'll be using this book as a quick reference when I need it for statistical methods that I frequently use.
1 of 2 people found the following review helpful. Ideal for the born-again statistician By enchanting505 I acquired an MA-level education that involved lots of study of econometrics (basically regression analysis using economic variables) 20-plus years ago. Unfortunately I hadn't used a lick of that knowledge until I was recently hired by a research org and felt the need to brush up on my stats and regression skills. This book, combined with a download of the R console, was my ticket to get back up and running with my new statistician peers. The author includes a lot of useful datasets, the most interesting to me being the student retention study which he indicates resulted in a very valuable real-life implementation at his institution. Yes, there are occasional disconnects between the R commands displayed and the output (some missing attach statements and load / read commands). That can be annoying but at least it makes you think when you enter those command and create output. If you're paying full freight for a hardcopy I can appreciate your concern over that (I read an online version), but if you would like to learn R and need to revisit the fundamentals like I did, this book is extremely useful.
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Beginning R: An Introduction to Statistical Programming, by Larry Pace, Joshua Wiley
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