Overview

This unit of study expands on earlier units in the program, 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.

Requisites

Prerequisites
STA60005 Statistical Practice 2
Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date

Learning outcomes

Students who successfully complete this unit will be able to:

  • Demonstrate professionally-relevant SAS programming and data management skills
  • Write SAS programs to enter, load, and merge different types of data from multiple sources
  • Visualise data graphically using SAS graphical procedures
  • Summarise data and perform descriptive statistical analyses using SAS procedures
  • Conduct parametric and non-parametric analysis of variance for balanced and unbalanced study designs using SAS and interpret the results
  • Perform linear regression analysis using SAS and interpret the results
  • Analyse data using generalised linear model (GLM) techniques using SAS

Teaching methods

Hawthorn Online

Type Hours per week Number of weeks Total (number of hours)
Online Contact (Phasing out)
Collaboration		1.00 6 weeks 6
Specified Learning Activities (Phasing out)
Various		3.00 12 weeks 36
Unspecified Learning Activities (Phasing out)
Independent Learning		9.00 12 weeks 108
TOTAL150

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
Face to Face Contact (Phasing out)
Seminar		3.00 12 weeks 36
Specified Learning Activities (Phasing out)
Various		2.00 12 weeks 24
Unspecified Learning Activities (Phasing out)
Independent Learning		7.50 12 weeks 90
TOTAL150

Assessment

Type Task Weighting ULO's
AssignmentIndividual 40% 2,3,4,5,6 
ExaminationIndividual 50% 4,5,6,7 
Online QuizzesIndividual 10% 1,2,4 

Content

  • 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.
  • Generalised linear models.

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.