- Docente: Lorenzo Mancini
- Crediti formativi: 4
- Lingua di insegnamento: Inglese
- Moduli: Lorenzo Mancini (Modulo 1) Cristina Poletti (Modulo 2)
- Modalità didattica: Convenzionale - Lezioni in presenza (Modulo 1) Convenzionale - Lezioni in presenza (Modulo 2)
- Campus: Bologna
-
Corso:
Laurea Magistrale in
Statistical Sciences (cod. 9222)
Valido anche per Laurea Magistrale in Statistical Sciences (cod. 9222)
Conoscenze e abilità da conseguire
By the end of the course, the student acquires the operational tools for the analysis of case studies and he is able to prepare reports by using SAS and to present them with the use of Microsoft Power Point.
Contenuti
- 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
- Introduction to stat procedures in SAS
Testi/Bibliografia
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.
Metodi didattici
- Computer laboratory sessions using SAS.
As concerns the teaching methods of this course unit, all students must attend Module 1, 2 on Health and Safety online
Modalità di verifica e valutazione dell'apprendimento
Students are requested to create work groups made of 3-4 individuals max. A project will be assigned to each group 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).
Strumenti a supporto della didattica
- Lab tutorials
- Slides
Orario di ricevimento
Consulta il sito web di Lorenzo Mancini
Consulta il sito web di Cristina Poletti