69844 - SAS Laboratory

Academic Year 2019/2020

  • Docente: Giulia Zardi
  • Credits: 6
  • Language: Italian
  • Moduli: Giulia Zardi (Modulo 1) Paola Scrigner (Modulo 2)
  • Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Statistics, Economics and Business (cod. 8876)

Learning outcomes

Al termine del corso, lo studente: - possiede gli strumenti operativi per l'analisi di casi studio in diversi ambiti applicativi - è in grado di redigere reports mediante l'utilizzo di R/SAS e Microsoft Power Point

Course contents

  • Overview of SAS 
  • Datasets, Libname, Syntax
  • Datasets import and structure
  • Proc Contents/Proc Print
  • Data types
  • Selection of observations, Operations on variables
  • Proc Sort, first., last.
  • Format, Informat, Proc Format
  • Proc Freq, Proc Univariate, Proc Means
  • Merge, Transpose
  • Creation of graphs using SAS
  • Proc Report, ODS

Readings/Bibliography

Handouts provided by the teacher.

Suggested reading:

  • Lora D. Delwiche, Susan J. Slaughter, The Little SAS Book: A Primer, Fifth Edition (English Edition) 5th Edition, 2012.


Teaching methods

  • Computer laboratory sessions (using SAS).

Assessment methods

Students are requested to create work groups made of 3-4 individuals max. Each group will choose among a list of projects provided by the end of the course. Each project will consists on a statistical analysis to be performed using SAS. A powerpoint document with analysis will be provided to the teacher before the exam.

The document must contain: 

  • analysis objectives;
  • description of the used dataset;
  • used SAS code; and
  • interpretation of the results.

The oral exam will consists of the powerpoint presentation of the analysis. The evaluation will be made on an individual basis (i.e. not group basis). In order to evaluate each student individually, extra questions on SAS programming can be asked during the session. 

Non-attending students can perform the task by choosing a dataset among those provided (RMK: write an e-mail to agree on the project before the exam).

Teaching tools

  • Lab tutorials
  • Slides

Office hours

See the website of Giulia Zardi

See the website of Paola Scrigner