Using R for Introductory Statistics (e-bog) af Verzani, John
Verzani, John (forfatter)

Using R for Introductory Statistics e-bog

546,47 DKK (inkl. moms 683,09 DKK)
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in...
E-bog 546,47 DKK
Forfattere Verzani, John (forfatter)
Udgivet 3 oktober 2018
Længde 518 sider
Genrer Probability and statistics
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781315362670
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version.See What's New in the Second Edition:Increased emphasis on more idiomatic R provides a grounding in the functionality of base R.Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible.Use of knitr package makes code easier to read and therefore easier to reason about.Additional information on computer-intensive approaches motivates the traditional approach.Updated examples and data make the information current and topical.The book has an accompanying package, UsingR, available from CRAN, R's repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="e;UsingR"e;)), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text.The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.