logo

EbookBell.com

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://ebookbell.com/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.

EbookBell Team

Introduction To Statistical Data Analysis For The Life Sciences 1st Edition Srensen

  • SKU: BELL-5308522
Introduction To Statistical Data Analysis For The Life Sciences 1st Edition Srensen
$ 31.00 $ 45.00 (-31%)

0.0

0 reviews

Introduction To Statistical Data Analysis For The Life Sciences 1st Edition Srensen instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 3.18 MB
Pages: 415
Author: Sørensen, Helle; Ekstrøm, Claus Thorn
ISBN: 9781439825556, 1439825556
Language: English
Year: 2011
Edition: 1

Product desciption

Introduction To Statistical Data Analysis For The Life Sciences 1st Edition Srensen by Sørensen, Helle; Ekstrøm, Claus Thorn 9781439825556, 1439825556 instant download after payment.

Any practical introduction to statistics in the life sciences requires a focus on applications and computational statistics combined with a reasonable level of mathematical rigor. It must offer the right combination of data examples, statistical theory, and computing required for analysis today. And it should involve R software, the lingua franca of statistical computing.
Abstract: Any practical introduction to statistics in the life sciences requires a focus on applications and computational statistics combined with a reasonable level of mathematical rigor. It must offer the right combination of data examples, statistical theory, and computing required for analysis today. And it should involve R software, the lingua franca of statistical computing

Related Products