Further Statistical Computing Using SAS
PostgraduateSWI-STA700032019
Course information for 2019 intake
Figure out ways to multiply your current skills and study further statistical computing. Use SAS to identify and analyse data. Calculate methods to apply techniques and interpret results to address theories.
Enrolments for this course are closed, but you may have other options to start studying now. Book a consultation to learn more.
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Entry requirements
- Part of a degree
- Duration
- -
- Loan available
- FEE-HELP available
Further Statistical Computing Using SAS
About this subject
Students who successfully complete this subject 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 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
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%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Prior study
You must have successfully completed the following subject(s) before starting this subject:
one of
- SWI-STA60005-Statistical Practice 2
SWI-HMS771 (Not currently available)
Equivalent subjects
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
SWI-HMS781 (Not currently available)
Additional requirements
- Other requirements -
- Other special requirement
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.