https://github.com/sassoftware/sas-prog-for-r-users
Teaching and lab materials for the "SAS Programming for R Users" course, including course notes, data, and code.
https://github.com/sassoftware/sas-prog-for-r-users
Last synced: 7 months ago
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Teaching and lab materials for the "SAS Programming for R Users" course, including course notes, data, and code.
- Host: GitHub
- URL: https://github.com/sassoftware/sas-prog-for-r-users
- Owner: sassoftware
- License: cc-by-4.0
- Created: 2016-10-24T16:58:01.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2024-08-16T14:09:59.000Z (about 1 year ago)
- Last Synced: 2025-02-13T13:24:46.492Z (9 months ago)
- Language: SAS
- Size: 14.8 MB
- Stars: 154
- Watchers: 25
- Forks: 75
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SAS Programming for R Users (Course Materials)
This project contains the learning materials for the free SAS programming course, _SAS Programming for R Users_.
SAS Training offers a free e-Learning version of this course, which includes lecture, demos, and exercises.
There are also occasionally instructor-led sessions of this course in the "Live Web" format for no charge; see
[the SAS training web site for the schedule and the Self-paced e-Learning link](https://support.sas.com/edu/schedules.html?id=3033).
## Materials Included:
The course materials supplied here contain everything you need for self-paced
learning or (for experts) to teach the course to other students. Materials
include:
- [PDF version of the course notes](notes/LWSP4R_001.pdf) (over 600 pages)
- Sample data files in CSV, XLSX, text, and SAS code formats
- Over 80 SAS programs for course exercises
## About The Course
This course is for experienced R users who want to apply their existing skills and extend them to the SAS environment.
Emphasis will be placed on programming and not statistical theory or interpretation. Students of this course should have knowledge of plotting, manipulating data, iterative processing, creating functions, applying functions, linear models, generalized linear models, mixed models, stepwise model selection, matrix algebra, and statistical simulations.
Learn how to:
- read and write SAS programs
- import various forms of data
- subset and merge data tables
- do iterative processing and simulate new data
- create new variables and functions
- create and enhance plots of all types
- apply descriptive and inferential procedures including regression,
logistic regression, analysis of variance,
stepwise model selection, and mixed models
- conduct matrix algebra and statistical simulations in the interactive matrix language (IML)
- call R from SAS to use as a complimentary resource.
## Lab Machine Configuration
The Live Web version of this course uses a virtual lab environment.
The lab environment features SAS for Windows, SAS Enterprise Guide,
and SAS Studio. Any of these can be used as the programming environment.
A small part of the course addresses the use of SAS Enterprise Miner.
Self-paced learners or anyone using this material in a classroom setting can
adapt the course to use their own instance of Base SAS (Display Manager),
SAS Enterprise Guide, or SAS Studio. SAS can run on Windows or any supported
variety of UNIX or Linux.
The SAS program examples assume a home directory of "`s:\workshop`" for the
SAS programs and data files. To adapt to your own environment, simply
change those path references to a location that works for your own
machine. If using SAS University Edition, you can use the
`/folders/myfolder` [shared folder structure](https://support.sas.com/software/products/university-edition/faq/shared_folder_whatis.htm)
as a "home base" for the code and data.
### SAS Products
The following SAS products are used for the bulk of the course:
- Base SAS
- SAS/STAT
- SAS/IML
These products are all [included with SAS University Edition](http://www.sas.com/en_us/software/university-edition.html),
a free SAS programming environment that you can download from SAS.
### Integration with R
Chapter 8 of this course (chapter title: "A Bridge between SAS and R")
shows examples of integrating R with SAS.
The integration with R requires an installed version of R,
plus a few additional configuration settings within
your SAS environment. These settings are described in Chapter 8 of the course
notes.
*Note:* Because you cannot modify its configuration, SAS University Edition
does not support integration with R. You will still be able to complete
Chapters 1 through 7 without the R integration.
# Licensing
You can obtain a copy of the license at [LICENSE.txt](https://github.com/sassoftware/sas-prog-for-r-users/blob/master/LICENSE)