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CO5124 - Data Analysis and Decision Modelling
| Credit points: | 3 |
| Year: | 2023 |
| Student Contribution Band: | Band 1 |
| Administered by: | College of Business, Law & Governance |
Businesses typically collect large volumes of data with relative ease. However data are often meaningless until they are analysed for trends, patterns and relationships and then become useful information. This subject is designed to provide an integrated knowledge for understanding and managing information resources, building basic business intelligent system, interpreting business statistics, and developing practical decision models. It will equip students with decision-making tools and illustrate their applications. Acting on information to develop solutions and support decision-making is a key business skill.
Learning Outcomes
- explain the importance of information as an organisational resource and to develop an appreciation for issues in managing data/information/knowledge;
- apply graphical and numerical tools for organising, analysing, interpreting, and presenting data;
- integrate the knowledge of Microsoft Excel and other application softwares with the knowledge of accounting and finance;
- design, build and test computer based models for planning, decision making and control of business problems, interpret model results, and make recommendations to stakeholders.
Subject Assessment
- Written > Business plan - (40%) - Individual
- Written > Case study analysis - (40%) - Individual
- Written > Project plan - (20%) - Individual.
| Assumed Knowledge: |
Capability with Excel or similar spreadsheet package |
| Inadmissible Subject Combinations: |
EC5203 CO5111 LB5002 CO5724 |
Availabilities |
|
| Cairns, Trimester 2, Internal | |
| Census Date 22-Jun-2023 | |
| Coordinator: | Dr Damien Wallace |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Trimester 1, Internal | |
| Census Date 09-Mar-2023 | |
| Coordinator: | Dr Singwhat Tee |
| Lecturer: | Ms Kathleen Arambulo. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Trimester 2, Internal | |
| Census Date 22-Jun-2023 | |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Brisbane, Trimester 3, Internal | |
| Census Date 05-Oct-2023 | |
| Coordinator: | Dr Singwhat Tee |
| Lecturer: | Ms Kathleen Arambulo. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Singapore, Study Period 51, Internal | |
| Census Date 06-Apr-2023 | |
| Coordinator: | Assoc. Professor Huiping Zhang |
| Lecturer: | Ms Daphne Yiu. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Singapore, Study Period 52, Internal | |
| Census Date 03-Aug-2023 | |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| JCU Singapore, Study Period 53, Internal | |
| Census Date 30-Nov-2023 | |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| Townsville, Trimester 2, Internal | |
| Census Date 22-Jun-2023 | |
| Coordinator: | Dr Singwhat Tee |
| Lecturers: | Mr Ian Burnett, Dr Damien Wallace. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| Trimester 2, External | |
| Census Date 22-Jun-2023 | |
| Coordinator: | Dr Singwhat Tee |
| Lecturer: | Dr Damien Wallace. |
| Workload expectations: |
The student workload for this 3 credit point subject is approximately 130 hours.
|
| Method of Delivery: | WWW - LearnJCU |
Note: Minor variations might occur due to the continuous Subject quality improvement process, and in case of minor variation(s) in assessment details, the Subject Outline represents the latest official information.