Price: $199.99 – $75.89
(as of Jan 22,2025 15:37:04 UTC – Details)
Publisher : Springer; 2nd ed. 2011 edition (July 26, 2011)
Language : English
Hardcover : 714 pages
ISBN-10 : 1461406846
ISBN-13 : 978-1461406846
Item Weight : 2.31 pounds
Dimensions : 6.25 x 1.5 x 9.25 inches
Customers say
Customers find that the book provides a good introduction and reference for R programming. They find it easy to read and understand, especially for SPSS or SAS users learning R. The book is useful for beginners, providing useful information like R-based IDEs. Customers appreciate the clear graphics and statistical analysis provided in the book.
AI-generated from the text of customer reviews
Are you a SAS or SPSS user looking to expand your statistical and computing skills? Look no further than the powerful programming language R. R is a free, open-source software that is widely used in the fields of statistics and data analysis.
In this post, we will explore how R can be a valuable tool for SAS and SPSS users looking to enhance their data analysis capabilities. R offers a wide range of packages and functions that make it easy to perform complex statistical analyses, create data visualizations, and manipulate data sets.
One of the key advantages of R is its flexibility and extensibility. With over 10,000 packages available on the Comprehensive R Archive Network (CRAN), users can easily find tools to suit their specific needs. Whether you are looking to conduct regression analysis, perform clustering, or create interactive plots, there is likely a package available in R that can help you achieve your goals.
Additionally, R has a strong community of users who contribute to the development of new packages and provide support through online forums and tutorials. This can be especially helpful for SAS and SPSS users who may be new to R and looking for guidance on how to get started.
Overall, R is a versatile and powerful tool that can complement the skills of SAS and SPSS users. By learning R, you can expand your repertoire of statistical techniques and enhance your ability to analyze and interpret data. So why not give R a try and see how it can take your data analysis to the next level?
#SAS #SPSS #Users #Statistics #Computing,machine learning: an applied mathematics introduction
