Difference between revisions of "R Crash Course"

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== Day 1 ==
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=== Day 1 ===
 
The following topics will be covered in this day:
 
The following topics will be covered in this day:
  
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- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
 
- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
  
== Day 2 ==
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=== Day 2 ===
 
The following topics will be covered in this day:
 
The following topics will be covered in this day:
  
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- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
 
- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
  
== Day 3 ==
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=== Day 3 ===
 
The following topics will be covered in this day:
 
The following topics will be covered in this day:
  
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- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
 
- Practice Session [http://osscom.org/sites/default/files/public/day01_day03_practice.r]
  
== Day 4 ==
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=== Day 4 ===
 
The following topics will be covered in this day:
 
The following topics will be covered in this day:
  
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== Datasets ==
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=== Datasets ===
 
   
 
   
 
* MPG [http://osscom.org/sites/default/files/public/mpg.csv]
 
* MPG [http://osscom.org/sites/default/files/public/mpg.csv]
 
* mydata100 [http://osscom.org/sites/default/files/public/mydata100.csv]
 
* mydata100 [http://osscom.org/sites/default/files/public/mydata100.csv]

Revision as of 12:44, 23 February 2016

Introduction

Learn the fundamentals of R the open source statistical computing and graphics environment and language.

R provides researchers and students with a wide variety of extensible data processing, statistical and graphical libraries.

This crash course is organized to be given as a series of seminars over the period of 4 days. Each day will include a practice session to practice some of the R commands.

Please use the accompanied datasets in order to be able to perform the associated exercises correctly.


Day 1

The following topics will be covered in this day:

  • Introduction to R
  • Introduction RStudio
  • Simple Data Import / Export Functionalities
  • Simple Statistical Operations Using R
  • Using R Help

- Simple R Script [1]

- Practice Session [2]

Day 2

The following topics will be covered in this day:

  • Introduction to R Programming
  • R Data Types
  • Control and Loop Structures
  • R Functions
  • Scoping

- Practice Session [3]

Day 3

The following topics will be covered in this day:

  • Creating Simple Graphs Using R
  • Customizing Graphs

- Practice Session [4]

Day 4

The following topics will be covered in this day:

  • Introduction to ggplot2 plotting package


- Practice Session [5]

- Extra Practices [6]


Datasets