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R for Everyone: Advanced Analytics and Graphics (AddisonWesley Data & Analytics Series),Used
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Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for nonstatisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone is the solution.Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality youll need to accomplish 80 percent of modern data tasks. Landers selfcontained chapters start with the absolute basics, offering extensive handson practice and sample code. Youll download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, youll construct several complete models, both linear and nonlinear, and use some data mining techniques.By the time youre done, you wont just know how to write R programs, youll be ready to tackle the statistical problems you care about most.Coverage Includes: Exploring R, RStudio, and R packages Using R for math: variable types, vectors, calling functions, and more Exploiting data structures, including data.frames, matrices, and lists Creating attractive, intuitive statistical graphics Writing userdefined functions Controlling program flow with if, ifelse, and complex checks Improving program efficiency with group manipulations Combining and reshaping multiple datasets Manipulating strings using Rs facilities and regular expressions Creating normal, binomial, and Poisson probability distributions Programming basic statistics: mean, standard deviation, and ttests Building linear, generalized linear, and nonlinear models Assessing the quality of models and variable selection Preventing overfitting, using the Elastic Net and Bayesian methods Analyzing univariate and multivariate time series data Grouping data via Kmeans and hierarchical clustering Preparing reports, slideshows, and web pages with knitr Building reusable R packages with devtools and Rcpp Getting involved with the R global community
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- Q: What is the main focus of 'R for Everyone: Advanced Analytics and Graphics'? A: The book focuses on teaching the basics of the R programming language, making it accessible for beginners and non-statisticians who want to perform statistical modeling and data analysis.
- Q: Is this book suitable for someone with no programming experience? A: Yes, 'R for Everyone' is designed for beginners, starting with fundamental concepts and gradually introducing more complex topics in a clear and intuitive manner.
- Q: What topics are covered in this book? A: The book covers a range of topics including data structures, statistical graphics, user-defined functions, linear and nonlinear modeling, and data manipulation techniques.
- Q: How many pages does 'R for Everyone' have? A: The book consists of 560 pages, providing comprehensive coverage of R programming and analytics.
- Q: What edition of the book is available? A: This is the second edition of 'R for Everyone', published on June 8, 2017.
- Q: Who is the author of 'R for Everyone'? A: The author is Jared P. Lander, a professional data scientist with extensive experience in teaching R to new users.
- Q: What type of binding does this book have? A: The book is available in paperback binding, making it easy to handle and read.
- Q: Are there practical exercises included in the book? A: Yes, the book includes extensive hands-on practice and sample code to help readers apply what they learn.
- Q: Can this book help in preparing for statistical analysis tasks? A: Absolutely, it focuses on the essential R functionality needed to tackle a wide range of statistical analysis tasks effectively.
- Q: Does 'R for Everyone' provide resources for further learning? A: Yes, the book encourages readers to engage with the R global community and includes guidance on building reusable R packages.