Students

BUSA8000 – Techniques in Business Analytics

2026 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Narges Safari
narges.safari@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
BUSA6004 or ECON6034 or (Admission to MBusAnalytics or MActPrac or GradCertResMQBS or GradDipResMQBS)
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit develops some of the core skills needed for the practice of modern business analytics. Statistical inference and associated statistical computing will be covered along with an introduction to analytical techniques needed for working with both structured and unstructured data. The reporting of the results from quantitative style research will also be studied.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Articulate the importance and application of data in a variety of contexts.
  • ULO2: Apply methods for handling data in relevant software.
  • ULO3: Implement statistical learning algorithms in relevant software.
  • ULO4: Apply appropriate statistical methods/models, and perform analysis on various types of data and interpret the result.
  • ULO5: Understand and apply the principles of statistical inference.
  • ULO6: Successfully work in teams to achieve group and organizational objectives

General Assessment Information

Late Submission Penalties

If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. Submissions more than 7 days late will receive a mark of 0.

Example 1 (out of 100):

If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.

Example 2 (out of 30):

If you score 27/30 but submit 20 hours late, you will lose 1.5 marks and receive 25.5/30.

 

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI assisted?
Professional practice: Exploratory data analysis 30% No 02/04/2026 Individual Yes Open AI
Skills development: Data analysis individual project 30% No 08/05/2026 Individual Yes Open AI
Professional practice: Analysis group project 40% No 29/05/2026 Individual and Group No Open AI

Professional practice: Exploratory data analysis

Assessment Type 1: Professional task
Indicative Time on Task 2: 15 hours
Due: 02/04/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: Yes
AI assisted?: Open AI

The purpose of this assessment is for you to focus on exploratory data analysis as a foundation for data analysis.

 

You will be given a dataset/business case and required to perform various analysis. Full details will be provided on iLearn.

 

Skills in focus:

  • Discipline knowledge
  • Digital skills
  • Critical thinking and problem solving
  • Communication skills 

 

Deliverable(s): Jupyter Lab file with solutions and recorded video explaining the solution (6 minutes).

Individual assessment
On successful completion you will be able to:
  • Articulate the importance and application of data in a variety of contexts.
  • Apply methods for handling data in relevant software.
  • Implement statistical learning algorithms in relevant software.
  • Apply appropriate statistical methods/models, and perform analysis on various types of data and interpret the result.

Skills development: Data analysis individual project

Assessment Type 1: Professional task
Indicative Time on Task 2: 20 hours
Due: 08/05/2026
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: Yes
AI assisted?: Open AI

The purpose of this assessment is for you to conduct data analysis to generate new insights for data-driven decision-making.

 

You will be given a dataset/business case and required to perform various analyses. Full details will be provided on iLearn.

 

Skills in focus:

  • Digital skills
  • Critical thinking and problem solving
  • Discipline knowledge 
  • Communication skills

 

Deliverable(s): Jupyter Lab file with solutions and recorded video explaining the solution (6 minutes).

Individual assessment
On successful completion you will be able to:
  • Articulate the importance and application of data in a variety of contexts.
  • Apply methods for handling data in relevant software.
  • Implement statistical learning algorithms in relevant software.
  • Understand and apply the principles of statistical inference.

Professional practice: Analysis group project

Assessment Type 1: Portfolio
Indicative Time on Task 2: 25 hours
Due: 29/05/2026
Weighting: 40%
Groupwork/Individual: Individual and Group
Short extension 3: No
AI assisted?: Open AI

The purpose of this assessment is for you to tackle a real-world business problem using industry-standard analytics techniques and Python programming.

 

You will work in a team to address a business scenario by conducting exploratory data analysis, performing statistical modelling, and developing a Python-based solution. Your team will present recommendations and rationale and submit a written report.

 

Skills in focus:

  • Digital skills
  • Critical thinking and problem solving
  • Collaboration and communication
  • Work readiness

 

Deliverable(s): Group presentation (10%, 15-minute presentation per team), Jupyter Lab file (20%) and individual written report (10%, max 500 words)

Individual and group assessment
On successful completion you will be able to:
  • Articulate the importance and application of data in a variety of contexts.
  • Apply methods for handling data in relevant software.
  • Implement statistical learning algorithms in relevant software.
  • Apply appropriate statistical methods/models, and perform analysis on various types of data and interpret the result.
  • Understand and apply the principles of statistical inference.
  • Successfully work in teams to achieve group and organizational objectives

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.

3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

Delivery and Resources

Delivery of this unit is in person in class. Please refer to iLearn for unit resources.

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2026.04 of the Handbook