This is the 1st course in my SAS training series. A Case Study at the end of the course will test your understanding!
Welcome! Get started with this online SAS tutorial to master SAS essentials and obtain SAS certification!
The lessons in this course are meant to be taken in order, as each lesson builds upon knowledge, and may mention some important ideas/concepts. If you skip videos, it may appear that some aspects are not being explained. For example, if you skip the import.txt lecture because you only care about importing .csv files, you may miss explanations about certain lines of codes.
Nevertheless, you will learn a lot about SAS programming!
You will learn how to code in the SAS statistical programming language, to help you start a career/gain employment, or move up at your current company. If you are studying SAS at a post-secondary institution, this course can not only help you with school projects but prepare you for a career after you complete your education.
Commercially, SAS is the most used programming language. It is a powerful statistical and data analytic tool which helps you with data entry, data management, anddata analysis. Every company needs a data ninja who is generally an expert in data management and data interpretation or analysis!
Let me tell you what you will learn in this tutorial. In the import section, you will learn how to import different file types (.txt, .csv, .xlsx); in working with data section, you will learn how to merge two data sets, filter observations, clean and reduce your data, read dates, create an enumeration variable, and much more. There is also a section on Informats/Formats and SAS Input Types (list input, column input, formatted input). In the arrays section, I will share some detail about arrays. As of now, I will show you how to use Arrays to recode variables and create new ones. In the Functions section, I will cover the Rand function, length/lengthn/lengthc functions, Trim function, compress function, input/put functions, catx function and more!
In the visualization section, you will learn how to make a scatterplot and bar charts. In the statistical (data) analysis section, you will learn types of data analysis methods and how to do data analysis and interpretation. Here, I will cover independent t-tests, chi-square analysis, linear regression, and multiple regression. I have also included a few concepts from Macro Programming. The course ends with a Case Study that is taken from the real-life application and lets you see how some of the concepts you learned about are integrated together!
Learning the SAS programming language means being able to accomplish the same goal on ANY software the supports SAS language. I personally use WPS. You guys have your own options.
Finally, you have nothing to lose. No risk! You get a 30-day money back guarantee + the course for life (including any new content added after you enroll)!
Enroll to master SAS programming today! Your future looks brighter with SAS training.
We are not in any way affiliated or associated with SAS Institute. We do not provide, nor do we endorse, a download of SAS University edition for your learning purposes, nor do we personally use SAS software, or SAS logos. We do not link to SAS website, nor do we link to any SAS content, nor do we have screen shots of any of their assets, nor do we distribute it, nor do we suggest its ours.
We use a commercial license from WPS. The system I use, WPS, is in no way associated with SAS System. Furthermore, whenever you see the phrases "SAS", "SAS Language" and "language of SAS" used in the course content this refers to the computer programming language. If you see phrases like "program", "SAS program", "SAS language program" used in my course, this is used to refer to programs written in the SAS language. These may also be referred to as "scripts", "SAS scripts" or "SAS language scripts".
About the Instructor
I've been a course instructor in the data science sphere for about 3 years. I have a particular passion for statistics/statistical programming and predictive modeling. I learned programming partly through school and partly self-teaching. At one point I was a Graduate student in Educational Psychology but decided at some point during that program that teaching and creating online content in the data science sphere was even a bigger passion.
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