This course is designed for beginners and improvers in the R language. Whilst previous programming experience or statistics knowledge is not required, it would be helpful.
• Introduction to R
• RStudio environment
• R Data Objects
• Using R Functions
• Writing R Functions
• Standard Graphics
• R Statistics
As with all our courses, attendees are provided with comprehensive training manuals complete with detailed examples and laminated tip sheets for future reference.
Introduction to the R language and the R community
This section will introduce R, its history and the S language and discuss how it is typically used.
• Introduction to R
• An introduction to the R community
• Online resources (such as R-Help)
• Internal/external support processes
The RStudio Environment
This section will introduce the RStudio GUI and will discuss the way we work in the RStudio environment.
• RStudio
• R Objects
• Workspace Objects
• The R Workspace
• R Packages
• The Script window
• Using the R help system
R Data Objects
This is a basic but vital section of the course, which introduces the base R data objects
• R data types
• Single mode structures: Vectors, Matrices and Arrays
• The relationship between single mode structures
• Multi mode structures: Lists and Data frames
• Factors (including the use of functions such as “cut” and “quantile”)
• Importing and Exporting data
Using R Functions
This section will concentrate on the basic structure of an R function
• The structure of a function (getting help, editing a function, seeing a function)
• Calling R functions
• Required, optional and dummy arguments (+ the ellipses)
• Functions for numeric data (inc. random number generation)
• Functions for character data
• Functions for logical/missing data
• Basic reporting and statistical functions
Writing R Functions
This section will introduce the building blocks of R function writing.
• The basic structure of an R function
• R function arguments
• Control structures: if, else and logical switching
• Using loops
Standard Graphics
In this section, we will introduce the basic concepts of producing graphical output in R
• Graphic devices
• Colours, Line Types, Plot Symbol, etc
• High level graphical functions and arguments
• Low level graphical functions
• Graphic parameters (the par function)
R Statistics
This section looks at statistical model fitting using the R class system
• Fitting a basic model using an R formula
• Investigating an R model object
• Worked examples
Pradžios data | Trukmė, d. | Kurso pavadinimas | Kaina, € | Statusas |
Užklausti | 2 | Introduction to R | € 1,000 | |
Užklausti | 2 | Introduction to Analytics with R | € 1,000 |