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Introduction to R
The Introduction to R course provides a practical introduction to the R environment to enable users to quickly become productive in the use of R.
Who Should Attend?
This course is appropriate for beginners and improvers in the R language
and is ideal for people wanting an all round introduction to R.
Course outline:
As with all our courses, attendees are provided with comprehensive training manuals complete with detailed examples and laminated tip sheets for future reference.
Should you want to book a place on this course or have any questions please contact us at
.
Should your organization have more than 3 possible attendees why not talk to us about hosting a customized and focused course delivered at your own premises?
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Course details:
Introduction to the R language and the R community
This section will introduce R, it’s history and the S language, and speak about how it is typically used.
- Introduction to R
- Comparisons with S-PLUS and SAS
- An introduction to the R community
- Online resources (such as R-Help)
- Internal/external support processes
- How R is used in your vertical industry
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The R Environment
This section will introduce the basic R syntax and will discuss the way we work in the R environment
- R Objects
- Search path, Working Directory
- Assigning and masking R objects
- Packages, Task Views
- Working with R editors
- Using the R help system
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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
- The S3 class system
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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)
- Lazy argument matching
- Functions for numeric data (inc. random number generation)
- Functions for character data
- Functions for logical/missing data
- Basic reporting and statistical functions
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The "apply" family of functions
This section will look at the need for, and the use of, the "apply" family of R functions
- The need for apply functions
- Structures with dimentions: The apply functions
- Operating on lists: lapply and sapply
- Operating on vectors: sapply
- The "by" statement: tapply and by
- Environment apply: eapply
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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 (and not using) loops
- Handling inputs (match.call etc)
- Handling outputs
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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)
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Advanced Graphics
The grid graphics system
- viewports : push, up, down, viewport trees
- graphical objects
- grid units
- The Lattice Package
- Create a trellis graphic, add information
- Use grid and lattice together
- Other graphical systems : ggplot, rgl
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R Statistics
This section looks at will look at statistical model fitting using the R class system
- Fitting a basic model using an R formula
- Investigating an R model object
- Worked examples to be guided by the customer
- Linear models
- Mixed models
- Survival analysis
- Missing data
- Generalised additive models
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