Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.
Please read the tutorial at this link. https://ebooknice.com/page/post?id=faq
We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.
For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.
EbookNice Team
Status:
Available4.7
31 reviewshttps://www.apress.com/gp/book/9781484260524
Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data).
Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, along with exercises to test your new knowledge. The text opens with a hands-on installation of R and CRAN packages for both Windows and macOS. The bulk of the book is an introduction to statistical methods (non-proof-based, applied statistics) that relies heavily on R (and R visualizations) to understand, motivate, and conduct statistical tests and modeling.
Beginning R 4 shows the use of R in specific cases such as ANOVA analysis, multiple and moderated regression, data visualization, hypothesis testing, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done.
You will:
Who This Book Is For
Programmers and data analysts who are new to R. Some prior experience in programming is recommended.