Unit Profile Correction added on 02-08-24
Assessment 2 Case study, Due Dates Change:
- Original Assessment Due Date: Week 7, Friday (30 August 2024), 11:45PM (AEST)
- NEW Due Date: Week 8, Friday (6 September 2024), 11:45PM (AEST)
- NEW Return Date to Students: Week 10, Friday (20 September 2024)
Assessment 3 Report, Due Date Change:
- Original Due Date: Week 12, Friday (4 October 2024), 11:45PM (AEST)
- NEW Due Date: Week 12, Sunday (6 October 2024), 11:45PM (AEST)
Overview
With today’s digitisation and technology development, many organisations can collect and consolidate tremendous amounts of data and store them in databases and data warehouses with ease. In business analytics, you will use a variety of computational techniques and/or methods to evaluate and analyse huge sources of data in real time for trends, patterns, classification, relationship, and other useful information. You will learn and examine data sets for statistical inference, and conduct quantitative analysis, predictive modelling, regression, data mining, and optimisation. This is a practical based core unit and will provide you with foundation knowledge to contribute to the use of various data analytics for problem solving.
Details
Pre-requisites or Co-requisites
STAT11048 Essential Statistics is an anti-requisite for this unit MGMT11169 Business Analytics. Students who completed STAT11048 Essential Statistics should not enroll in this unit MGMT11169 Business Analytics.
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 2 - 2024
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Undergraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Class Timetable
Assessment Overview
Assessment Grading
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of 'pass' in order to pass the unit. If any 'pass/fail' tasks are shown in the table above they must also be completed successfully ('pass' grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the 'assessment task' section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University's Grades and Results Policy for more details of interim results and final grades.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure - Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure - International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback - Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from Student Unit and Teacher Evaluation (SUTE)
The vast quantity of online resources help students in complete weekly activities and assessments.
Continue to update online resource to include more case studies from different industry sectors.
Feedback from Student Unit and Teacher Evaluation (SUTE)
The real-world applications provided were helpful in deepening our understanding of the material.
Continue to update relevant and real-world applications.
- Analyse and reflect on key concepts of business analytics
- Apply quantitative tools and techniques to analytically identify, examine, investigate and propose solutions to business problems
- Synthesise data from a variety of sources and develop models to address practical problems in industry.
Alignment of Assessment Tasks to Learning Outcomes
| Assessment Tasks | Learning Outcomes | ||
|---|---|---|---|
| 1 | 2 | 3 | |
| 1 - Presentation - 20% | |||
| 2 - Case Study - 40% | |||
| 3 - Report - 40% | |||
Alignment of Graduate Attributes to Learning Outcomes
| Graduate Attributes | Learning Outcomes | ||
|---|---|---|---|
| 1 | 2 | 3 | |
| 1 - Communication | |||
| 2 - Problem Solving | |||
| 3 - Critical Thinking | |||
| 4 - Information Literacy | |||
| 5 - Team Work | |||
| 6 - Information Technology Competence | |||
| 7 - Cross Cultural Competence | |||
| 8 - Ethical practice | |||
| 9 - Social Innovation | |||
| 10 - Aboriginal and Torres Strait Islander Cultures | |||
Textbooks
Business Analytics
5th edition (2024)
Authors: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann
Cengage Learning
Boston Boston , MA , US
ISBN: 978-0-357-90220-2
Binding: Paperback
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- Excel spreadsheet software
All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)
For further information, see the Assessment Tasks.
s.kuik@cqu.edu.au
Module/Topic
Data Analytics and Excel Fundamentals
Chapter
Business analysis and decision making; and Lecture notes and material are available in Moodle
Events and Submissions/Topic
Details of Moodle site and resources available.
Expectations of student engagement with the unit.
Overview of the Assessment Items.
Module/Topic
Descriptive Statistics
Chapter
Data types and statistics; and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Data Visualisation
Chapter
Charts and data visualisation; and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Data Interpretation and Strategies
Chapter
Importance of Data Insights and Communication
Events and Submissions/Topic
Module/Topic
Modelling Uncertainty and Probability
Chapter
Probability and modelling uncertainty and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
No classes will be held during this week.
Chapter
No classes will be held during this week.
Events and Submissions/Topic
Module/Topic
Continuous Probability Distributions
Chapter
Modelling real world phenomena using continuous probability distributions and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Discrete Probability Distributions
Chapter
Modelling real world phenomena using descrete probability distributions and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Statistical Inference and Sampling
Chapter
Understanding of point Estimation and sampling process and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Hypothesis Testing
Chapter
Understanding of types of errors and hypothesis testing and and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Modelling of Linear Regression
Chapter
Regression modelling and relationships; and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Model Reporting and Analysis
Chapter
Understanding of model analysis and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Business Analytics in Practice
Chapter
Business case applications and and Lecture notes and material are available in Moodle.
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
Module/Topic
Chapter
Events and Submissions/Topic
1 Presentation
You are required to prepare and deliver a 10-minute oral presentation on a data analytics case application. The case application should demonstrate your ability to analyse a dataset, extract meaningful insights, and present your findings in a clear and engaging manner. This assessment aims to evaluate your technical understanding of data analytics, your ability to interpret and visualize data, and your presentation skills. The case application and information will be provided on the unit website.
Week 6 Friday (23 Aug 2024) 11:45 pm AEST
The oral assessment will be held in Week 6. Further information will be provided on Moodle in Week 3.
Week 8 Monday (2 Sept 2024)
Grades and feedback comments are released on the unit Moodle page.
- Demonstrates critical thinking by providing insightful data analysis and innovative perspectives: 20%
- Demonstrates understanding of utilising software and solving numerical problems: 20%
- Demonstrates knowledge and understanding of model content, integrating key concepts and theories: 20%
- Exhibits communication and presentation skills with clear, confident, and engaging speech, effectively conveying ideas: 40%
- Analyse and reflect on key concepts of business analytics
2 Case Study
The assessment evaluates students' proficiency in applying fundamental data analytics techniques using Excel spreadsheet. Students will analyse a provided case study and numerical data file (available on the unit website) and subsequently write a clear and concise 1500-word data analytics report. Students' submissions must include a concise data analytics report, an Excel spreadsheet and/or relevant calculations, and a cover sheet with the following information: unit name and number, assessment number, students' names, and student numbers. The submission assesses students' ability to leverage data analytics techniques to drive business solutions
Week 7 Friday (30 Aug 2024) 11:45 pm AEST
Further information will be provided on Moodle in Week 3.
Week 9 Monday (9 Sept 2024)
Grades and feedback comments are released on the unit Moodle page.
Your report analysis, recommendations and presentation will be assessed according to the following criteria.
- Demonstrated understanding of data analytics with techniques and/or tools that are related to the questions posed: 25%
- Accurately suggest and develop the model for detailed analysis in relation to the questions posed: 25%
- Able to articulate and evaluate case studies to provide managerial insights and practical limitations based on quantitative outcomes: 20%
- Provide appropriate and well-structured, concise and clear expression of decision-making arguments: 10%
- Provide a clear flow of thought throughout the business report, evidenced by succinct Executive Summary, Introduction, and Conclusion: 10%
- Adherence to APA Reference format: 5%
- Clarity of written expression, grammar, spelling: 5%
Report length 1500-words. (penalty of 1% per 100-words that exceed the maximum 1575-words). However, the summary, table of contents, reference list and appendices are excluded from a report’s word count.
Submissions must be in Business Report format using Word with 1.5 line spacing and Times Roman 12-point font.
Late submissions will also be penalised at the rate of "five percent of the total marks available for the assessment each calendar day (full or part) it is overdue" (Policy: Assessment of Coursework section 3.2.4)
- Analyse and reflect on key concepts of business analytics
- Apply quantitative tools and techniques to analytically identify, examine, investigate and propose solutions to business problems
- Synthesise data from a variety of sources and develop models to address practical problems in industry.
3 Report
This assessment evaluates students' mastery of data analytics techniques and business problem solving skills, as applied through the utilization of Excel spreadsheet software. Students are required to complete an in-depth analysis of a business application and scenario, accompanied by a numerical data file (accessible on the unit website), and subsequently write a clear and concise 1600-word data analytics report. Submissions must include a concise data analytics report, an Excel spreadsheet and/or calculations, and a cover sheet with the following information: unit name and number, assessment number, students' names, and student identification numbers.
Week 12 Friday (4 Oct 2024) 11:45 pm AEST
Assessment feedback and grades are to be released upon certification of grades (refer to assessment policy).
Your report analysis, recommendations and presentation will be assessed according to the following criteria.
- Demonstrated understanding of data analytics with techniques and/or tools that are related to the questions posed: 25%
- Accurately suggest and develop the model for detailed analysis in relation to the questions posed: 25%
- Able to articulate and evaluate case studies to provide managerial insights and practical limitations based on quantitative outcomes: 20%
- Provide appropriate and well-structured, concise and clear expression of decision-making arguments: 10%
- Provide a clear flow of thought throughout the business report, evidenced by succinct Executive Summary, Introduction, and Conclusion: 10%
- Adherence to APA Reference format: 5%
- Clarity of written expression, grammar, spelling: 5%
- Report length 1600-words. (penalty of 1% per 100-words that exceed the maximum 1680-words). However, the summary, table of contents, reference list and appendices are excluded from a report’s word count.
Submissions must be in Business Report format using Word with 1.5 line spacing and Times Roman 12-point font.
Late submissions will also be penalised at the rate of "five percent of the total marks available for the assessment each calendar day (full or part) it is overdue" (Policy: Assessment of Coursework section 3.2.4)
- Apply quantitative tools and techniques to analytically identify, examine, investigate and propose solutions to business problems
- Synthesise data from a variety of sources and develop models to address practical problems in industry.
As a CQUniversity student you are expected to act honestly in all aspects of your academic work.
Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.
When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.
Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.
As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.
What is a breach of academic integrity?
A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.
Why is academic integrity important?
A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.
Where can I get assistance?
For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.
What can you do to act with integrity?
