The book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio functionality to ease their development efforts. Familiarity with R is assumed. Those who want to get started with R development using RStudio will also find the book useful. Even if you already use R but want to create reproducible statistical analysis projects or extend R with self-written packages, this book shows how to quickly achieve this using RStudio.
- Significant experience in providing expert level technical leadership for statistical analysis projects and providing solutions to highly complex problems.
Statistical analysis projects kean university college essay
If you would like to be part of an outstanding group of people working on world-class research and clinical trials; if you would like to help advance data management and statistical analysis projects as we work together to achieve better health options for all—consider joining our team.
What you’ll learn: Quickly and efficiently create and manage statistical analysis projects, import data, develop R scripts, and generate reports and graphicsThe rationale for developing ESS is that most statistical analysis systems provide a more or less sophisticated graphical user interface (GUI). However, their full power is only available using their scripting language. Furthermore, complex statistical analysis projects require a high degree of automation and documentation which can only be handled by creating statistical analysis scripts. Unfortunately, many statistics packages provide only weak text editor functionality and show major differences between them. Without a unified text editor user interface additional effort is required from the user to cope with limited functionality and with text editor differences.