Course Description
This short course is designed for explain the practical applications and use of R and R Studio (an integrated development environment, IDE, for R) effectively in the shortest possible time. It provides a solid conceptual understanding of both how R works and how to produce effective results.
R is a programming language and environment commonly used in statistical computing, data analytics and scientific research. It is one of the most popular languages used by statisticians, data analysts, researchers and marketers to retrieve, clean, analyze, visualize and present data. Its use is near universal when developers and administrators are looking to do analysis of data.
RStudio is an integrated development environment (IDE) for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
R comprises:
- The R programming language, designed specifically for working with statistical analysis and data analysis;
- The R environment, designed for effective handling and storage of large data sets; and
- A massive on-line repository of R packages which cover advanced statistical modeling, machine learning, data visualization and data manipulation tools, as well as packages that support analyses in specific domains such bio-statistics, financial modeling, population studies and computational physics.
Learning Outcomes
- Customize the R environment and use the various help and assistance tools to support working with R and simplify analysis workflows.
- Conduct basic R programming, including how to write simple, efficient and effective R scripts to automate the data analysis workflow.
- Perform data manipulation using R.
- Appreciate how to use the R data structures, such as data frames, to access, store, arrange and organize data sets.
- Perform data analysis with R, including the use of the core R facilities for statistical analysis and graphics for data visualization.
Prerequisites
- No prior programming knowledge is necessary.
Who Should Attend
- Anyone interested in learning how to use R and RStudio.
