introduction to r (lect 1)

8/11/2019 Introduction to R (LECT 1)

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D R . S O H A I L A K R A M

INTRODUCTION TO R


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R

R is a computer language that allows the user to programalgorithms and use tools that have been programmed byothers.

R was originally written by Ross Ihaka and Robert Gentleman,at the University of Auckland.

It is an implementation of the S

language, which wasprincipally developed by John Chambers.


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R

R is an Open Source (and freely available)environment for statistical computing and graphics.

The Comprehensive R Archive Network (CRAN) linksprovide binary downloads for Windows, for Mac OSX and for several flavours of Linux.

Source code is also available.


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R

R is under active development - typically two majorreleases per year.

R provides data manipulation, display facilities andmost statistical procedures. It can be extended withpackages containing data, code anddocumentation.

Currently there are more than 2400 contributedpackages in the CRAN.


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R HISTORY

Statistical programming language S developed atBell Labs in 1976 (at the same time as UNIX)

Intended to interactively support research and

data analysis projects Exclusively licensed to Insightful ( S-Plus ) R: Open source platform similar to S developed by

R . Gentleman and R. Ihaka (U of Auckland, NZ)

during the 1990s Since 1997: international R-core developing team Updated versions available every couple months


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WHAT CAN YOU DO WITH R ?

You can ... do calculations

perform statistical analysis (using availablecode)

create powerful graphics

write your own functions


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WHAT R IS AND WHAT IT IS NOT

R is a programming language a statistical package

an interpreter Open Source

R is not a database a collection of black boxes a spreadsheet software package commercially supported


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OPEN SOURCE

Provides full access to algorithms and their implementation. Gives you the ability to fix bugs and extend software. Provides a forum allowing researchers to explore and expand

the methods used to analyze data Is the product of thousands of leading experts in the fields they

know best. Ensures that scientists around the world - and not just ones in

rich countries - are the co-owners to the software toolsneeded to carry out research.

Promotes reproducible research by providing open andaccessible tools.

Most of R is written in R! This makes it quite easy to see whatfunctions are actually doing.


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R ADVANTAGES

Fast and free. State of the art: Statistical researchers provide their

methods as R packages. SPSS and SAS are years

behind R! 2nd only to MATLAB for graphics. Mx, WinBugs, and other programs use or will use R . Active user community Excellent for simulation, programming, computer

intensive analyses, etc. Forces you to think about your analysis. Interfaces with database storage software (SQL)


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R DISADVANTAGES

Not user friendly @ start - steep learning curve,minimal GUI.

No commercial support; figuring out correct

methods or how to use a function on your own canbe frustrating. Easy to make mistakes and not know these mistakes. Working with large datasets is limited by RAM Data prep & cleaning can be messier & more

mistake prone in R vs. SPSS or SAS


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R VS COMMERCIAL PACKAGES

Many different datasets (and otherobjects) available at same time

Datasets can be of any dimension

Functions can be modified

Experience is interactive, youprogram until you get exactly whatyou want

One datasets available at agiven time

Datasets are rectangular

Functions are proprietary

Experience is passive-youchoose an analysis and theygive you everything they thinkyou need


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R VS COMMERCIAL PACKAGES

One stop shopping - almostevery analytical tool you canthink of is available

R is free and will continue toexist. Nothing can make it goaway, its price will neverincrease.

Tend to be have limited scope,forcing you to learn additionalprograms; extra options cost moreand/or require you to learn adifferent language (e.g., SPSSMacros)

They cost money. There is noguarantee they will continue toexist, but if they do, you can betthat their prices will always increase


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INSTALLING R

Go to http://cran.r-project.org/ and select either:

MacOS X

Windows and base

Select to download the latest version: 2.14.1

Install and Open.
http://cran.r-project.org/http://cran.r-project.org/http://cran.r-project.org/http://cran.r-project.org/http://cran.r-project.org/http://cran.r-project.org/


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GETTING STARTED

The R GUI.


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R PACKAGES

Applications of R normally use a package; i.e., alibrary of special functions designed for a specificproblem.

Hundreds of packages are available, mostly writtenby users. A user normally only loads a handful of packages

for a particular analysis(e.g., library(MASS)).

Standards determine how a package is structured,works well with other packages and creates newdata types in an easily used manner.

Standardization makes it easy for users to learn new

packages.

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