26777 Data Processing Using SAS
Warning: The information on this page is indicative. The subject outline for a
particular session, location and mode of offering is the authoritative source
of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.
Subject handbook information prior to 2024 is available in the Archives.
Credit points: 3 cp
Subject level:
Postgraduate
Result type: Grade and marksThere are course requisites for this subject. See access conditions.
Anti-requisite(s): 260777 Data Processing Using SAS
Description
In the fourth industrial revolution, data has become one of our most precious goods. It’s available and cheap and holds promise for enterprises that want to gain a competitive edge. However, raw data are also commonly incomplete, unstructured and inconsistent. The subject Data Processing with SAS looks at how this widely used tool can transform a raw dataset into valuable information for exploring business performance and for decision making. SAS is the market leader software for analytics, being used by more than 83,000 business, government and university sites around the world, including 92 of the top 100 companies on the 2018 Fortune Global 1000®. This subject provides the fundamentals required for the SAS certification Base Programming Specialist. Students learn about data validation and manipulation. Data validation is the process of converting raw data into quality data by addressing issues such as missing values. Data manipulation, using methods such as coding, makes data easier to read and analyse. Finally, students learn how to apply the appropriate statistical tools to extract valuable information from real datasets.
Subject learning objectives (SLOs)
| 1. | Access and import different types of data within the SAS environment |
|---|---|
| 2. | Explore, validate and manipulate data for analyses |
| 3. | Run simple analyses, export the results and create reports |
Contribution to the development of graduate attributes
The subject introduces students to data processing, which is a fundamental step of Data Science. This subject gives students opportunities to develop their knowledge and proficiency in operating in the SAS environment. The learning activities enable students to develop and apply data analysis skills to real-world scenarios. Their business practice skills are further developed through learning activities related to the creation of reports. This subject is therefore aligned with the following Graduate Attribute(s):
- Intellectual rigour and innovative problem solving
- Professional and technical competence
Teaching and learning strategies
The teaching and learning approach comprises a combination of face-to-face and online learning activities. Students will be required to complete pre-work activities before coming to class. Three face-to-face workshops take place in a computer lab, for a hands-on experience where students will have opportunities to learn and practice using the SAS software.
Pre-class activities: Students are expected to read online content (readings and video tutorials), provided via the learning management system, prior to attending classes. They are also required to complete practice quizzes prior to each class in the learning management system, which will help identify possible gaps on the weekly topics and inform the class discussion. A mandatory, on-line formative assessment completed after the first lecture, will provide students with further feedback in week 4 to help direct their self-study.
Workshops: Face-to-face computer lab workshops are designed to present the theory and practice associated with using SAS. Students will use the software to manipulate and analyse data.
Feedback: Individual feedback will be provided after the formative on-line assessment after Lecture 1. General feedback based on performance in the pre-class practice quizzes will be given at the beginning of Lectures 2 and 3. Finally, students will receive formal feedback on assessment task 1 prior to the submission of assessment task 2.
Content (topics)
- Understanding of SAS environment
- Accessing and importing different types of data
- Data exploration and validation
- Data preparation
- Data analysis
- Exporting results and reporting data
Assessment
Assessment task 1: Computer-based Data Analysis (Individual)
| Objective(s): | This addresses subject learning objective(s): 1 and 2 |
|---|---|
| Weight: | 50% |
| Criteria: | Students will be assessed on their ability to explore different types of data sets by validating and preparing relevant data for the analysis through steps of:
Each question will require specific “data steps” to reproduce the expected outcome. Students will need to filter definite rows using conditional processing (i.e., if…, then…), to sort data appropriately as well as to format different data types such as dates. The outcome generated depends on the correctness of all the above-mentioned steps. |
Assessment task 2: Computer-based Data Analysis and Reporting (Individual)
| Objective(s): | This addresses subject learning objective(s): 2 and 3 |
|---|---|
| Weight: | 50% |
| Criteria: |
|
Minimum requirements
Students must achieve at least 50% of the subject’s total marks.
Required texts
There is no required textbook. However, it is recommended students become familiar with SAS learning material available online at https://www.sas.com/en_au/learn/academic-programs/resources/free-sas-e-learning.html.
References
- Prudhomme G. (2018). Business Data Processing. Arcler Press. ISBN-10: 1773614479
- Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning. Springer. ISBN: 9780387848570
- SAS e-learning: https://www.sas.com/en_au/learn/academic-programs/resources/free-sas-e-learning.html