1. Início
  2. NOVA Information Management School
  3. Pós-Graduação em Sistemas Estatísticos
  4. Pós-Graduação em Sistemas Estatísticos com Especialização em Estatísticas de Bancos Centrais
  5. Estatística Computacional I

Estatística Computacional I

Objetivos

At the end of this course, students should be able to:

  1. Read and create data files
  2. Read, create and combine SAS files
  3. Create variables using the assignment statement and conditional processing
  4. Manipulate data using SAS functions
  5. Processing data through DO cycles and arrays
  6. Create different types of reports
  7. Create formats with the FORMAT procedure
  8. Produce simple statistical analyses
  9. Convert numeric and alphanumeric data

Caracterização geral

Código

400005

Créditos

6.0

Professor responsável

Frederico Miguel Campos Cruz Ribeiro de Jesus

Horas

Semanais - A disponibilizar brevemente

Totais - A disponibilizar brevemente

Idioma de ensino

Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês

Pré-requisitos

Not applicable.

Bibliografia

  • SAS® 9.3 Language Reference: Concepts. Second Edition. Cary, NC: SAS Institute Inc. 2010.
  • SAS® 9.3 Language Reference: Dictionary. Third Edition. Cary, NC: SAS Institute Inc. 2010.
  • Base SAS® 9.3 Procedures Guide: Statistical Procedures. Third Edition. Cary, NC: SAS Institute Inc. 2010.
  • SAS® 9.3 Output Delivery System: User¿s Guide. Cary, NC: SAS Institute Inc., 2009.
  • Lora D. Delwiche; Susan J. Slaughter; Exercises and Projects for The Little SAS® Book, Fifth Edition (2015); SAS Institute
  • Lora D. Delwiche; Susan J. Slaughter; The Little SAS® Book: A Primer, Fifth Edition (2012); SAS Institute
  • Lora D. Delwiche; Susan J. Slaughter; The Little SAS® Enterprise Guide® Book (2017); SAS Institute
  • Ron Cody; Learning SAS® by Example: A Programmer's Guide (2007); SAS Institute
  • Support documents

Método de ensino

The curricular unit is based on mix of theoretical lectures and practical classes. Each session will introduce new concepts and methodologies, as well as the applications of the learnt concepts using different computational tools. Different learning strategies will be used, such as lectures, slide show demonstrations, step-by-step tutorials on how to approach practical examples, questions, and answers.

The practical component is focused in exploring the different computational tools by the students, including a discussion on the best approach under different scenarios.

Método de avaliação

Final exam (100%) in both evaluation calls.
 

Conteúdo

The course is organized in seven Learning Units (LU):

LU1. Introduction to the SAS System

  • Interface and basic concepts
  • SAS programs
  • SAS data sets
  • SAS data libraries

LU2. Data access

  • Reading data from unstructured files
  • Entering data directly in the program
  • Reading data from structured files

LU3. Data modification

  • Reading an existing data set
  • Variable selection
  • Observation selection
  • Descriptive labels
  • Creating variables and assigning values
  • SAS functions
  • Creating variables conditionally
  • Using a value in a later observation

LU4. Combining data sets

  • Concatenating data sets
  • Merging data sets

LU5. Production of reports

  • Simple reports
  • Displaying totals and subtotals
  • Processing groups of data
  • Titles, formats and labels

LU6. Some statistical procedures

  • PROC FREQ
  • PROC MEANS
  • PROC UNIVARIATE
  • PROC TABULATE
  • PROC CORR
  • PROC NPAR1WAY (self-study)

LU7. Advanced topics in data modification

  • Exporting SAS data
  • Converting character and numeric data
  • Simultaneous creation of multiple data sets
  • Processing data with DO loops
  • Processing data with arrays
  • SQL procedure