Subject details

Students who successfully complete this subject will be able to:

  1. Demonstrate professionally relevant SAS programming and data management skills
  2. Write SAS programs to enter, load, and merge different types of data from multiple sources
  3. Visualise data graphically using SAS graphical procedures
  4. Summarise data and perform descriptive statistical analyses using SAS procedures
  5. Conduct parametric and non-parametric analysis of variance for balanced and unbalanced study designs using SAS and interpret the results
  6. Perform linear regression analysis using SAS and interpret the results
  7. Analyse count data using generalised linear model (GLM) techniques using SAS.
    • The SAS Display Manager
    • Inputting temporary and permanent SAS datasets
    • Data Manipulation and transformation including date variables
    • Data Summaries and Graphics: PROC FREQ, PROC MEANS, PROC TABULATE, PROC SQL and, PROC SGPLOT.
    • Statistical Analysis for group comparisons: PROC UNIVARIATE, PROC TTEST, PROC ANOVA, PROC GLM and PROC NPAR1WAY
    • Linear regression: PROC CORR, PROC REG
    • Generalized linear models: PROC GENMOD

  • Study resources

    • Instructional methods

      • Discussion forum/Discussion Board
      • Online Quizzes/Tests
      • Online assignment submission
      • Web links

    • Print materials

      • Welcome letter

    • Online materials

      • Printable format materials

Equivalent subjects

You cannot enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:

  • SWI-HMS781

You must have successfully completed the following subject(s) before starting this subject:

SWI-STA60005-Statistical Practice 2 , or SWI-HMS771

Special requirements

  • OtherDetails -
    • Other special requirement

Please note: This subject was previously titled Further Statistical Computing 

This subject expands on earlier subjects in the degree, introducing students to other aspects of statistical computing. In particular, students will be introduced to one of the leading statistical software packages SAS - a powerful tool for organising and analysing data. Students will use this statistical software to further develop their knowledge in data management, data presentation, and statistical analysis.

Please note: assessment values are indicative only, details will be advised at the start of the subject.

  • Quiz — Online (10%)
  • Invigilated Exam (50%)
  • Assignments — 2 (40%)

Textbook information is pending.

Textbook information is pending.

Related degrees

postgraduate SWI-STA-GDI-2019

Graduate Diploma of Applied Statistics

postgraduate SWI-STA-MAS-2019

Master of Applied Statistics