Quantitative Research Methods provides training in the gathering, description and analysis of quantitative information in a broad range of different disciplines including, science, arts, sports, business, management and the financial sciences. Further, students use the skills acquired in this course to identify problems, interpret and analyse results, and provide solutions while engaging with external stakeholders.
This is a course in research methods including discussions, analysis, interpretation and providing solutions of: data gathering issues and techniques; sources of data and potential biases; graphical and numerical data description techniques including simple linear regression, sampling behaviour of averages and the Central Limit Theorem; point and interval estimation procedures; concepts in hypothesis testing for comparing two populations, simple and multiple linear regression; p-values and significance levels.
Students in this course are exposed to a variety of different problems/issues from different disciplines and seek to provide input to these problems through the application of quantitative data analysis skills. The data sets and/or problems/issues are introduced through a variety of guest speakers that are included in the class, as well as a series of recordings, blogs or newspaper articles to drive and contextualise the data stemming from the variety of different disciplines.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Use the skills developed in this course to identify problems in a variety of different disciplines to interpret and analyse results and provide solutions while engaging with external stakeholders and students from a variety of disciplines.
- Work collaboratively in groups from different areas of study to analyse results, provide solutions and orally present findings and discussions to a diverse range of stakeholders from different disciplines.
- Compare and contrast different sampling methodologies and assess suitability for a range of situations and contexts.
- Discuss different types of variables and produce appropriate graphical and numerical descriptive statistics.
- Apply probability rules and concepts to discrete and continuous random variables, including estimation techniques and the Central Limit Theorem, to solve problems across a range of disciplines.
- Perform and interpret hypothesis tests and linear regression analyses, including both simple and multiple regression.
- Use technology to perform statistical analysis, and interpret statistical software output in a variety of different fields of study.
Other Information
Indicative Assessment
- The research-based assessment will consist of assignments, providing students with a confined set of datasets along with a pertinent problem from the particular discipline that the dataset is relevant to. The objective of this assessment is to work collaboratively in groups to analyse and draw meaningful conclusions from data presented in graphical format. In this task, students will demonstrate in groups their ability to extract key information from data and communicate findings in a short, in-person oral group presentation. (10) [LO 1,2,3,4]
- The other assessment may include but is not restricted to: exams, quizzes, presentations and other assessments as appropriate. (90) [LO 1,2,3,4,5,6,7]
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Students are expected to commit at least 10 hours per week to completing the work in this course. This will include at least 3 contact hours per week and up to 7 hours of private study time.
Requisite and Incompatibility
Prescribed Texts
Information about the prescribed textbook will be available via the class summary.
Majors
Minors
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 1
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 2941 | 23 Feb 2026 | 02 Mar 2026 | 31 Mar 2026 | 29 May 2026 | In Person | N/A |
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 7912 | 27 Jul 2026 | 03 Aug 2026 | 31 Aug 2026 | 30 Oct 2026 | In Person | N/A |