SAS is an integrated software for advanced analytics, business intelligence, data management, and predictive analysis. This workshop introduces the basic elements of the SAS Software useful to write SAS programs to access, explore, prepare, and analyse data.
Cody R. (2015). An Introduction to SAS® University Edition, Cary, NC: SAS Institute Inc.
SAS Institute Inc. (2019). SAS® Certified Specialist Prep Guide: Base Programming Using SAS® 9.4. Cary, NC: SAS Institute Inc. OpenIntro Labs (https://www.openintro.org/stat/labs.php?stat_lab_software=SAS)
Further material will be suggested during the workshop.
By the end of this course, you will know how to use SAS Studio to write and submit SAS programs that access SAS, Microsoft Excel, and text data. You will know how to explore and validate data, prepare data by subsetting rows and computing new columns, analyze and report on data, export data and results to other formats
Students should have experience using computer software. Specifically, you should be able to understand file structures and system commands on your operating systems and access data files on your operating systems. No prior SAS experience is needed.
Lectures and lab sessions
The students will need their laptop with the free version of SAS installed, i.e. the SAS University Edition (https://www.sas.com/en_us/software/university-edition.html).
Modalità di verifica apprendimento
The objective of the final exam is to test students' practical skills acquired during the workshop. The final exam will be a set of exercises and problems to be solved using SAS.
Programma del corso
Introduction to the SAS University Edition. The SAS Studio Interface. Importing Your Own Data. Creating Reports. Summarizing Data Using SAS Studio. Graphing Data. An Introduction to SAS Programming. Reading Data from External Files. Reading and Writing SAS Data Sets. Creating Formats and Labels. Performing Conditional Processing. Performing Iterative Processing: Looping. Working with SAS Dates. Subsetting and Combining SAS Data Sets. Describing SAS Functions. Working with Multiple Observations per Subject. Describing Arrays. Displaying Your Data. Summarizing Data with SAS Procedures. Computing Frequencies.