Monday, July 19, 2010

Using R for Data Management, Statistical Analysis and Graphics soon to start shipping

Our newest book, Using R for Data Management, Statistical Analysis and Graphics, is anticipated to soon start shipping from Amazon, CRC Press, and other fine retailers.



The book complements our existing SAS and R book, particularly for users less interested in SAS. It presents an easy way to learn how to perform an analytical task in R, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation and vast number of add-on packages. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics.

Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The text includes convenient indices organized by topic and R syntax, and presents example analyses that employ a single data set from the HELP study to demonstrate the R code in action and facilitate exploration. We also provide several case studies of more complex applications. Data sets and code are available for download on the book’s website.

To book tries to lucidly summarize the aspects of R most often used by statistical analysts. We believe that new users of R will find the simple approach easy to understand while more sophisticated users will appreciate the invaluable source of task-oriented information.

Note as of August, 2010: the book is now shipping from Amazon, with a discounted price.

3 comments:

Milk Trader said...

Is it gonna be available in Kindle version?

Ken Kleinman said...

Possibly. We're working on it!

Unknown said...

Qualitative methods are most certainly a more appropriate option when in need of researching patterns and attitudes in customer behavior, understand the depth of the environment around the customer, and understand the cultural characteristics then influence a customer - especially when the marketer is not familiar with the country of culture. See more raw data for statistical analysis