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:

1. 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.
2. 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.
3. Compare and contrast different sampling methodologies and assess suitability for a range of situations and contexts.
4. Discuss different types of variables and produce appropriate graphical and numerical descriptive statistics.
5. 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.
6. Perform and interpret hypothesis tests and linear regression analyses, including both simple and multiple regression.
7. Use technology to perform statistical analysis, and interpret statistical software output in a variety of different fields of study.

Research-Led Teaching

In order to investigate new fields, make sense of new areas and tackle new problems, we need appropriate tools to explore and summarise data, graphically and numerically, and make decisions using the data under uncertainty. This course will use examples from varied areas to introduce statistical tools, methods and ways of thinking to students and prepare them for future courses, work and research projects. Students will have access to talks by guest speakers from industry who will share their experience in working with real data in the workplace.

Examination Material or equipment

The final exam will be centrally timetabled by Examinations, Graduations & Prizes prior to the examination period and will be held in person on campus. The final exam is an invigilated in-person exam. Please check ANU Timetabling for further information. Students will be supplied by ANU with an HP 300S+ Scientific Calculator for use in the final exam. Personal calculators are not permitted. Dictionaries of any form are not permitted.

Required Resources

All course notes and materials will be provided via the course page.

 This course will use Microsoft Excel to view data sets, perform some calculations and generate graphs. The software can be accessed for free by ANU students here:

https://services.anu.edu.au/information-technology/software-systems/microsoft-office-365. Microsoft Excel is required for the In-Tutorial Data Analysis Task.

You will also need access to a calculator to complete some exercises for this course.

Recommended Resources

Below are recommended resources for this course:

1. Black, K., Asafu-Adjaye, J., Burke, P., Khan, N., King, G., Perera, N., Papadimos, A., Sherwood, C., & Wasimi, S. (2024). Business Analytics and Statistics, 2nd Edition (2nd ed.). John Wiley & Sons, Incorporated. Library link: https://anu.primo.exlibrisgroup.com/permalink/61ANU_INST/1alil8h/alma991027091776507631
2. Berenson, M. (2019). Basic business statistics : concepts and applications (Fifth edition.). Pearson Australia. Library link: https://anu.primo.exlibrisgroup.com/permalink/61ANU_INST/1alil8h/alma991026838266807631
3. Lock, R. H. (2013). Statistics : unlocking the power of data. Wiley. Library link: https://anu.primo.exlibrisgroup.com/permalink/61ANU_INST/1csbe8o/cdi_nii_cinii_1130282272448857856

Staff Feedback

Students will be given feedback in the following forms in this course: 

?                To the whole class during lectures.

?                Within tutorial groups.

?                Individually during consultation hours

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Assessment Requirements

Any student identified, either during the current semester or in retrospect, as having used ghost writing services will be investigated under the University’s Academic Misconduct Rule.

As a further academic integrity control, students may be selected for a 15 minute individual oral examination of their written assessment submissions.

Scaling

Your final mark for the course will be based on the raw marks allocated for each of your assessment items. However, your final mark may not be the same number as produced by that formula, as marks may be scaled. Any scaling applied will preserve the rank order of raw marks (i.e. if your raw mark exceeds that of another student, then your scaled mark will exceed the scaled mark of that student) and may be either up or down.

Support for Students

The University offers a number of support services for students. Information on these is available online from http://students.anu.edu.au/studentlife/

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Pre-recorded Lecture 1/ Workshop 1Introduction: Basic Statistical Concepts and Collecting DataCreating Data Summaries: Organising and Visualising DataIntroduction to Microsoft Excel
2	Pre-recorded Lecture 2/ Workshop 2Creating Data Summaries: Numerical Descriptive Measures(Tutorials begin)	Online Quiz 1
3	Pre-recorded Lecture 3 / Workshop 3 Probability	Group Presentation: Finalise same-tutorial team formation by Friday, 5pm
4	Pre-recorded Lecture 4 / Workshop 4Discrete Probability Distributions
5	Pre-recorded Lecture 5 / Workshop 5Continuous Probability Distributions	Online Quiz 2In-Tutorial Data Analysis Task
6	Pre-recorded Lecture 6 / Workshop 6Sampling DistributionsConfidence Interval Estimation
7	Pre-recorded Lecture 7 / Workshop 7Confidence Interval EstimationHypothesis Testing - describing a single population
8	Pre-recorded Lecture 8 / Workshop 8Hypothesis Testing - describing a single population	Online Quiz 3
9	Pre-recorded Lecture 9 / Workshop 9Hypothesis Testing - comparing two populations	In-tutorial Group Presentation
10	Pre-recorded Lecture 10 / Workshop 10Simple Linear Regression	In-tutorial Group Presentation
11	Pre-recorded Lecture 11 / Workshop 11Simple Linear RegressionMultiple Linear Regression	In-tutorial Group PresentationOnline Quiz 4
12	Pre-recorded Lecture 12 / Workshop 12Additional Hypothesis Tests: ANOVA (Multiple Populations) Chi-Squared Tests (Categorical Data)	In-tutorial Group Presentation

Tutorial Registration

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.

Tutorials will be held weekly on campus (starting from week 2). Tutorial registration will be available two weeks prior to the beginning of the semester and will close at the end of

week 1. More details can be found on the Timetable webpage (https://www.anu.edu.au/students/program-administration/timetabling).   All students must enrol in a tutorial in order to complete the In-Tutorial Data Analysis Task and the Group Presentation. Tutorials will cover the previous week's pre-recorded lecture and workshop material.

Assessment Summary

Assessment task	Value	Due Date	Return of assessment	Learning Outcomes
Online Quizzes (on Canvas)	10 %	06/03/2026	29/05/2026	1,2,3,4,5,6,7
In-Tutorial Data Analysis Task	15 %	23/03/2026	31/03/2026	1,4,5,7
Group Presentation	15 %	04/05/2026	29/05/2026	1,2,3,4,6,7
Final Exam	60 %	04/06/2026	02/07/2026	1,2,3,4,5,6,7

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

Assessment Requirements

The ANU is using 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. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Canvas’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Course content delivery will take form of pre-recorded weekly lectures available on Canvas, a weekly face-to-face workshop (recorded and available via echo360 on the course page) and weekly on-campus tutorials. In-person tutorials are not recorded under any circumstances. Weekly consultations with the lecturer and the tutors will be conducted in-person or over Zoom. If conducted over Zoom, a Zoom link will be provided on Canvas.

Students are expected to have viewed the pre-recorded lecture prior to the weekly workshop on Monday. The pre-recorded lecture will be uploaded by 5pm on the Thursday of the week prior to the scheduled workshop.

Attendance at lectures and tutorials, while not compulsory, is expected in line with “Code of Practice for Teaching and Learning”, clause 2 paragraph (b).

Examination(s)

The final exam will be centrally timetabled by Examinations, Graduations & Prizes prior to the examination period. Please check ANU Timetabling for further information. The examination is invigilated by the ANU Examinations Office.

Assessment Task 1

Online Quizzes (on Canvas)

Four online quizzes will be conducted via the course website in Canvas at the end of Weeks 2, 5, 8 and 11 respectively. The quiz will open on Friday at 9:00am at the end of each respective week, and close on the following Monday at 11:59pm. That is, each quiz will be open for a 4-day period. Once the quiz is started it will need to be completed in the set time period. One attempt per quiz is permitted. 

Each quiz will contribute 2.5% towards the final mark for a total of 10%. The coverage of the quiz will be communicated to you in workshops and announced on Canvas on the Monday prior to the quiz opening for that week.

All quizzes are compulsory and not redeemable. All quizzes are to be completed individually.

The expected time allowed for each quiz is 30 minutes. Each quiz will consist of ten multiple choice questions or short-answer calculation questions. Each question in each quiz will be presented on a separate page and students can navigate backwards and forwards through the quiz. Some quizzes may require the student to download an Excel dataset and use technology to perform statistical analysis. All quizzes are open book and all materials are permitted (including the use of artificial intelligence tools). No invigilation software will be used for the quizzes.

Solutions and marks will be released upon the close of each quiz. Extensions for quizzes are not permitted under any circumstances.

Assessment Task 2

In-Tutorial Data Analysis Task

This assessment will be held in tutorials in Week 5 and will be conducted via the course website on Canvas. The assessment will be set up as a quiz and will require you to download an Excel dataset and answer the quiz questions related to the dataset as given to you. This will be an exercise in basic data manipulation, calculation of summary statistics, basic graph generation and interpretation of analytical questions. A sample data analysis task will be uploaded for you by the end of Week 2.

The time allowed for the data analysis task is 30 minutes. The data analysis task is worth 15% of the overall score in the course. The assessment is compulsory and is not redeemable. It is a closed-book assessment. Students must use the ANU computer in the computer lab. Use of your own personal device is not permitted. Use of artificial intelligence tools is strictly prohibited. Use of an alternative software package other than Excel to analyse the data is not permitted. Communication with other students or external parties during the assessment is strictly prohibited. At any time, (both during and after the assessment), the downloaded dataset must not be sent to any other persons or uploaded to any other platform, server, website, system, repository, app or software environment. The assessment will be invigilated by the tutor. Violation of these assessment conditions will be investigated according to ANU Procedure on academic integrity.

Students MUST sit the data analysis task in the tutorial they are enrolled in, otherwise the assessment will not count.

Students may request an Assessment Extension if they are unable to complete the assessment on their enrolled tutorial date due because of exceptional circumstances beyond their control. To be considered, a student must submit an Assessment Extension Request (using the link on the Canvas site), by 5pm on the day prior to your enrolled tutorial in Week 5. Assessment extension requests received after this time will be rejected. Submission of an extension request does not guarantee the extension will be approved. Extension requests will be reviewed by the course convenor in accordance with ANU Procedure: Student assessment (coursework).

If an extension request is approved by the course convenor, the student must complete the data analysis assessment in Week 6 at a date and time set by the course convenor. This date and time will not be assigned or changed to fit the schedule of individual students. Failure to attend the new assigned date in Week 6 will result in a grade of 0 for this assessment.

Assessment Task 3

Group Presentation

This assessment is to be completed in teams of 3 or 4 students from the same tutorial. Students can choose their own teams but all members must be from the same tutorial. Team formation must be finalised by 5pm Friday, Week 3. The assessment cannot be done individually in order to fulfill Learning Outcome 2.

Groups will be required to source a dataset of their choice and provide an analysis of their chosen dataset using the statistical concepts and methods from the course. Each group must run at least two different statistical hypothesis tests to answer research questions of their choice based on their chosen dataset. Groups will need to perform exploratory data analysis and decide on what data summaries and graphical displays to produce. Groups will be prepare a 15 minute presentation to communicate their project findings. Detailed instructions on the presentation requirements will be made available on Canvas by the end of Week 1.

Presentations will occur during tutorial times from Weeks 9 to 12 (inclusive). The order of team presentations will be randomly determined by your tutor after teams are finalised by Friday, Week 3.

All team members must be present and actively participate in their assigned tutorial presentation. Switching tutorials or presentation times is not allowed. Unexplained absence or lack of participation will result in a mark of zero for that member and may affect the other team members’ grades depending on the circumstances.

Written presentation slides must be fully typed and submitted via Turnitin on Canvas by 9am on the day of your presentation.

This group presentation is worth 15% of the overall score in the course. The group presentation is compulsory and is not redeemable.

If a team member encounters exceptional circumstances beyond their control such that they are unable to present on their assigned presentation date, this will affect the entire team. The team presentation can only go ahead if all team members are present. So team members must communciate with each other and decide whether or not to submit an Assessment Extension Request (using the link on the Canvas site). An Assessment Extension Request must be received by 5pm on the day prior to your assigned presentation date. Assessment extension requests received after this time will be rejected. Submission of an extension request does not guarantee the extension will be approved. Extension requests will be reviewed by the course convenor in accordance with ANU Procedure: Student assessment (coursework).

If an extension request is approved by the course convenor, the entire team will be rescheduled to present, at a date and time and location set by the course convenor. This date and time will not be assigned or changed to fit the schedule of individual students or teams. Failure to attend the new assigned date will result in a grade of 0 for this assessment for all group members.

Assessment Task 4

Final Exam

A compulsory final examination will be held during the university examination period at the end of semester. The exam will be held in-person on campus and will cover the entire syllabus. Students may bring in one A4 page (double-sided) of notes, either hand-written or typed, to the exam.

No dictionaries or personal calculators are allowed in the final exam.

In the final exam, each student will be supplied with an HP 300S+ Scientific Calculator.

The exam will be centrally timetabled. Details of the final examination timetable will be made available on the ANU Timetabling website. The onus is upon students to acquire their own scheduling details.

The final exam is worth 60% of the overall score in the course and is compulsory.

The exam duration will be 2 hours. The final exam may consist of multiple choice questions, short-answer calculation questions and short-answer written questions. Students will be required to submit working for some questions, as specified in the assessment. All work must be the students' own. Further details on the exam (duration, format, permitted materials) will be made available by the end of Week 10. Practice exams will be made available on Canvas by the end of Week 10.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

The group presentation is to be submitted online via the appropriate activity on the Canvas course page. You will be required to electronically sign an academic integrity declaration as part of the submission of your group presentation. Please keep a copy of the presentation for your records. 

Hardcopy Submission

There are no hard copy assignment submissions in this course

Late Submission

No submission of assessment tasks without an extension after the due date will be permitted. If an assessment task is not submitted by the due date, a mark of 0 will be awarded.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material. Any use of artificial intelligence must be properly referenced. Failure to properly cite use of Generative AI will be considered a breach of academic integrity.

Returning Assignments

Group presentation feedback will be returned via the appropriate activity on the Canvas course page.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

It will not be possible for presentations to be resubmitted.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Accessibility for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students