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EncartaLabs

# R Analytics

( Duration: 2 Days )

R is a free software programming language and a software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. The striking difference between R and most other statistical packages is that it is free software and that it is maintained by scientists for scientists.

The R Analytics training course will provide concepts and practical approach to the statistical package R which is becoming a industry standard for machine learning and data mining. This course lays the foundation to aspiring data scientists. After completion of the class, you will be able to apply statistical techniques to the data and derive meaningful information. The techniques learned in R Analytics course will help in Marketing, Insurance and Financial analysis in various IT organizations. R is currently used in Big data environments as well. This course will provide foundation to the advanced data management techniques.

• Basic school level – Maths and Statistics knowledge

This R Analytics workshop is intended for:

• Developers working in Business Intelligence space who are aspiring to become Data scientist, Techno Managers, Business Analysts
• SAS developers who are trying to migrate to open source technologies
• Msc Math and/or Statistics students with some programing background aspiring to become data scientist

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## A few concepts before starting

• How R works
• Creating, listing and deleting the objects in memory
• The on-line help
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## Data with R

• Objects
• Saving data
• Generating data
• Regular sequences
• Random sequences
• Manipulating objects
• Creating objects
• Converting objects
• Operators
• Accessing the values of an object: the indexing system
• Accessing the values of an object with names
• The data editor
• Arithmetic and simple functions
• Matrix computation
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## Graphics with R

• Managing graphics
• Opening several graphical devices
• Partitioning a graphic
• Low-level plotting commands
• Graphical parameters
• A practical example
• The grid and lattice packages
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## Statistical analyses with R

• A simple example of analysis of variance
• Formulae
• Generic functions
• GLM
• E1071
• KSVM
• KNN
• Dimensionality reduction
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## Programming with R in practice

• Loops and vectorization
• Writing a program in R