Quantitative Methods in Commerce G (11405.2)

Please note these are the 2024 details for this unit
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Quantitative Methods in Commerce G
Available teaching periods Delivery mode Location
View teaching periods Online
On-campus
 Bruce, ÃØÃÜÖ±²¥
EFTSL Credit points Faculty
0.125 3 Faculty Of Business, Government & Law
Discipline Study level HECS Bands
ÃØÃÜÖ±²¥ Business School Graduate Level Band 1 2021 (Commenced After 1 Jan 2021)
Band 1 2021 (Commenced Before 1 Jan 2021)
This unit highlights the importance of mathematical and statistical methods and tools for today's managers and analysts, and demonstrates how to apply these methods to business problems using real-world data. The quantitative skills that students learn in this unit are useful in all areas of business. Students learn how to model and analyse relationships within business data; how to identify appropriate statistical techniques; how to compute statistics by calculator and Microsoft Excel; how to interpret results in the context of the business problem; and how to forecast using business data. The unit is taught through data-driven examples, exercises and business case studies. The unit content includes working with equations and graphs of straight lines, linear programming, quantitative research principles in collecting, summarising and displaying business data, index numbers, relations in categorical data, measures of association, fitting straight lines, elementary probability concepts, the normal distribution and its business applications.

Learning outcomes

Upon successful completion of this unit, students will be able to:
1. Demonstrate an ability to solve a range of business problems by firstly synthesising, organising data, then analysing plus interpreting data and information in relation to specific topics, such as discounted cash flows and linear programming problems with at least 2 dimensions;
2. Clearly communicate to stakeholders the implications of the results of various techniques applied, as well as being able to identify and articulate the potential impacts of assumptions made and limitations of the techniques;
3. Explain how data is sampled, collected and presented using a range of summary measures;
4. Identify problems within real-world constraints and collect data for business decision making;
5. Create statistical models for studying relationship among business variables;
6. Demonstrate an ability to select appropriate techniques when dealing with unfamiliar problems in business, finance and economics, as well as structure a given problem scenario in a way that allows solution via appropriate techniques; and
7. Demonstrate the application of forecasting method. Students will also be able to articulate the impacts of the assumptions behind, and limitations of, these models.


Graduate attributes

1. UC graduates are professional - communicate effectively
1. UC graduates are professional - display initiative and drive, and use their organisation skills to plan and manage their workload
1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
3. UC graduates are lifelong learners - adapt to complexity, ambiguity and change by being flexible and keen to engage with new ideas


Prerequisites

None.

Corequisites

None.

Incompatible units

11165 Quantitative Methods in Commerce, 5123 Business Statistics

Equivalent units

6275 Statistical Analysis & Decision Making G

Assumed knowledge

Basic mathematics approximately to Year 10 standard.
Availability for enrolment in 2025 is subject to change and may not be confirmed until closer to the teaching start date.
Year Location Teaching period Teaching start date Delivery mode Unit convener
2024 Bruce, ÃØÃÜÖ±²¥ Semester 1 05 February 2024 Online Dr Jinjing Li
2024 Bruce, ÃØÃÜÖ±²¥ Semester 1 05 February 2024 On-campus Dr Jinjing Li
2024 Bruce, ÃØÃÜÖ±²¥ Semester 2 29 July 2024 On-campus Dr Jinjing Li
2025 Bruce, ÃØÃÜÖ±²¥ Semester 1 03 February 2025 On-campus Dr Jinjing Li
2025 Bruce, ÃØÃÜÖ±²¥ Semester 2 28 July 2025 On-campus Dr Jinjing Li
The information provided should be used as a guide only. Timetables may not be finalised until week 2 of the teaching period and are subject to change. Search for the unit timetable.

Required texts

Main textbook (recommended):

               Title: Business Analytics and Statistics, 2nd Edition

               Publisher: John Wiley and Sons Australia

               Author: Black et al

               ISBN: 9781394189670

Recommended reference:

              Title: Business Analytics and Statistics Abridged Australia/New Zealand, Edition 8

              Publisher: Cengage Learning Australia

              Author: Selvanathan et al

              ISBN-10: 0170439542 or ISBN-13: 9780170439541

Submission of assessment items

Special assessment requirements

Final grades in this subject will be assessed according to performance in each of the assessment items identified above. In order to pass this unit, you must obtain:

  • an overall total score of at least 50% AND
  • submit all assessment items marked as mandatory AND
  • obtain a minimum of 40% in the final exam.

For assessment items marked as mandatory, each piece of assessment must be completed and submitted, but  it is not necessary that students pass each individual item of assessment unless otherwise stated. 

Students are not allowed to use generative artificial intelligence (GenAI) in assessments for this unit.

The University's position is that artificial intelligence services must not be used for assessment or assessment preparation by students unless explicitly allowed in the assessment instructions for an assessment task published with the assessment task and/or in the unit outline. That is, an AI service may only be used if:

a) its use is authorised by the unit convener as part of the specified task; and
b) it is used in the way allowed in the assessment instructions and/or unit outline; and
c) its use is appropriately referenced, meaning that the students must reference the use of AI in their assessment in the same way as they reference other source material.

The use of AI has not been specified in the assessment instructions for the unit or in the unit outline and thus, AI is not a permissible resource.

Students must apply academic integrity in their learning and research activities at UC. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.

Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.

UC students have to complete the annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).

UC uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.

Information is provided in the Academic Integrity Policy, Academic Integrity Procedure, and University of ÃØÃÜÖ±²¥ (Student Conduct) Rules 2023. For further advice, visit Study Skills.

Participation requirements

Students are highly encouraged to attend all academic sessions. Attendance and active participation will enhance your understanding of the unit content and, therefore, the quality of your assessment responses. A lack of participation may result in an inability to satisfactorily pass assessment items

Required IT skills

This unit requires practical skills in Microsoft Excel, such as using formulas and key functions, along with general computer literacy. Students are encouraged to build or refresh these skills through online resources if needed before starting the unit.

Additionally, this unit may involve the use of Virtual Room in your UCLearn teaching site. The Virtual Room allows you to communicate in real time with your lecturer and other students. To participate verbally, rather than just typing, you will need a microphone. For more information and to test your computer, go to the Virtual Room in your UCLearn site and 'Join Course Room'. This will trigger a tutorial to help familiarise you with the functionality of the virtual room.

Work placement, internships or practicums

None

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