Here is a brief introduction about R and SAS,instructions about installations and a broad high‐level comparison.
SAS used to be called the Statistical Analysis System Software suite developed by the SAS Institute for advanced analytics, business intelligence, data management, and predictive analytics. Developed at North Carolina State University from 1966 until 1976, when the SAS Institute was incorporated. It was then further developed in the 1980s and 1990s with the additional statistical procedures and components. SAS is a language, a software suite and a company created by Anthony James Barr and James Goodnight along with two others. For purposes of this book we will use SAS for SAS computer language.
While a graduate student in statistics at North Carolina State University, James Goodnight wrote a computer program for analyzing agricultural data. After a few years, James's application had attracted a diverse and loyal following among its users, and the program's data management and reporting capabilities had expanded beyond James's original intentions.
In 1976, he decided to work at developing and marketing his product on a full‐time basis, and the SAS Institute was founded. Since its beginning, a distinguishing feature of the company has been its attentiveness to users of the software. Today, the SAS Institute is the world's largest privately‐held software company, and Dr. James Goodnight is its CEO. He continues to be actively involved as a developer of SAS System software as well as being one of the most widely respected CEOs in the community.
The SAS System has more than 200 components
The SAS University Edition includes the SAS products Base SAS®, SAS/STAT®, SAS/IML®, SAS/ACCESS® Interface to PC Files, and SAS Studio. SAS has an annual license fee and almost 98% return to SAS every year, voting by their chequebook. All these products are Copyright © SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513, USA. (https://decisionstats.com/2009/08/20/the‐top‐decisionstats‐articles‐part‐1‐analytics/and https://en.wikipedia.org/wiki/SAS_(software))
While SAS Software for Enterprises is priced at an annual license, for students, researchers and learners you can choose from the SAS University Edition (a virtual machine) at https://www.sas.com/en_in/software/university‐edition.html or SAS on Demand at https://odamid.oda.sas.com/SASLogon/login (a software as a service running SAS in browser).
To install the SAS University Edition on your Virtual machine you can follow the following steps (I am using VMware Workstation for this):
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. R was initially written by Robert Gentleman and Ross Ihaka.
From https://www.r‐project.org/about.html, R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes:
There are almost 14 000+ packages in R (https://www.rdocumentation.org). You can also look at specific views of packages (https://cran.r‐project.org/web/views is a task view like a bundle or cluster of packages with similar usage i.e. econometrics). For computationally‐intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.
You can download and install R from https://www.r‐project.org (or specifically from https://cloud.r‐project.org for your operating system). You can then download and install the IDE RStudio from https://www.rstudio.com/products/rstudio/download/#download. Lastly, you can install any of 12 000+ packages (see https://cran.r‐project.org/web/views and https://www.rdocumentation.org) using install.packages(“PACKAGENAME”) from within R. These packages can be downloaded from the CRAN (Comprehensive R Archive Network).
Within https://www.datacamp.com/community/tutorials/r‐packages‐guide, R packages are collections of functions and datasets developed by the community. They increase the power of R either by improving existing base R functionalities, or by adding new ones. For example, you can use sqldf package to use SQL with R and RODBC package to connect to RDBMS databases.
In addition, an excellent resource is how to learn SAS for R users from the SAS Institute itself.
https://support.sas.com/edu/schedules.html?ctry=us&crs=SP4R
The e‐learning course is free as of October 2018. The course teaches the following:
data ajay;
set input;
run;
R has functions and packages for similar functions bundled together
A Proc by Proc comparison in SAS language with R language functions is shown below. It will be explained in greater detail in later chapters. Some people consider R's smaller syntax helpful in coding while others consider SAS to be easier to learn and focus on analysis instead.
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In this chapter we have introduced R and SAS languages, and briefly compared their main functions/syntax.
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