The R Project for Statistical Computing
R is a free software environment for statistical computing and graphics.
It compiles and runs on a wide variety of UNIX platforms, Windows and
MacOS.
Duration: 16 Hours
The R tool is an open sourced framework which grew as a result of a strong push by Google. Today, R is poised to overtake SAS as the most widely used tool in statistical analyses and with over 20,000 packages currently available, it has near limitless potential for business application.
Module 1: Basic R tool programming
R environment and Windows system
R Objects, Data permanency and removing objects
R Help and search with Functions
R commands and Case sensitivity
Data Import and Export
Packages
R Studio Installation
Simple Manipulations : Numbers and Vectors
Writing your own functions
Module 2: Advanced Applications of R
Data Manipulation: merging, sorting, filtering, de-duping
User defined functions
Visualizations: histogram, bar plot, box plot, mosaic plots, geographic plots, etc
TM package
Word cloud Package
Module 3: Hands on
In Class Project
Students do independent research
Build your first sentiment analysis algorithm
Combine solutions of students to showcase a final project
Duration: 16 Hours
The R tool is an open sourced framework which grew as a result of a strong push by Google. Today, R is poised to overtake SAS as the most widely used tool in statistical analyses and with over 20,000 packages currently available, it has near limitless potential for business application.
Module 1: Basic R tool programming
R environment and Windows system
R Objects, Data permanency and removing objects
R Help and search with Functions
R commands and Case sensitivity
Data Import and Export
Packages
R Studio Installation
Simple Manipulations : Numbers and Vectors
Writing your own functions
Module 2: Advanced Applications of R
Data Manipulation: merging, sorting, filtering, de-duping
User defined functions
Visualizations: histogram, bar plot, box plot, mosaic plots, geographic plots, etc
TM package
Word cloud Package
Module 3: Hands on
In Class Project
Students do independent research
Build your first sentiment analysis algorithm
Combine solutions of students to showcase a final project
The R Project for Statistical Computing
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