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Introduction to R Programming: An Essential Statistical Tool for Data Analysis

Understand the fundamentals of R: a statistical computing system with powerful tools for data analysis, matrix calculations, and visualization. Learn to use R packages, create arrays, load datasets, and more for effective data handling. Includes examples and resources for further exploration.

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Introduction to R Programming: An Essential Statistical Tool for Data Analysis

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  1. The R Projectfor statistical computing Eric Fouh, Christopher Poirel CS 5604 Fall 2010

  2. What is R?

  3. Usages of R • statistics system • data handling and storage facility • calculations on arrays, in particular matrices • integrated collection of tools for data analysis • graphical tool for data analysis • programming language (called ‘S’)

  4. Structure of R • R functions and dataset are stored in packages • R is provided with 25 “standard” packages: • Hundreds of contributed packages (written by different authors ) are available

  5. R and Information Retrieval

  6. Getting started with R • To start R >R • To quit R >q() • To see installed packages >library() • To load a package >library(class) • To start help > help.start() • To create a vector > x <- c(10.4, 5.6, 3.1, 6.4, 21.7) • To create a matrix > x <- array(1:20, dim=c(4,5)) # Generate a 4 by 5 array filled with number from 1 to 20. • To display an object >x • To delete an object >rm x • To load data from file >HousePrice <- read.table("houses.data")

  7. Examples (1) • Term-Document Matrix

  8. Examples (1)

  9. Examples (2) • Eigenvalues and eigenvectors

  10. Examples(3)

  11. Examples(3) • Law Rank approximation

  12. Examples(3)

  13. Examples(3)

  14. Resources • IIR Book • http://www.r-project.org/ Questions?

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