CQUniversity Unit Profile
MGMT11169 Business Analytics
Business Analytics
All details in this unit profile for MGMT11169 have been officially approved by CQUniversity and represent a learning partnership between the University and you (our student).
The information will not be changed unless absolutely necessary and any change will be clearly indicated by an approved correction included in the profile.
General Information

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

Career Level: Undergraduate
Unit Level: Level 1
Credit Points: 6
Student Contribution Band: 10
Fraction of Full-Time Student Load: 0.125

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 1 - 2023

Brisbane
Melbourne
Online
Rockhampton
Sydney

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).

Class and Assessment Overview

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

Bundaberg, Cairns, Emerald, Gladstone, Mackay, Rockhampton, Townsville
Adelaide, Brisbane, Melbourne, Perth, Sydney

Assessment Overview

1. Online Quiz(zes)
Weighting: 30%
2. Online Test
Weighting: 30%
3. Online Test
Weighting: 40%

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.

Previous Student Feedback

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 Unit Evaluation

Feedback

Using an Excel spreadsheet for complex data analytics with key mathematical principles might be difficult for students who have never worked with this software before.

Recommendation

The weekly lesson plans will include more Excel spreadsheet exercises to help students learn how to use Excel for complex data analysis.

Feedback from Unit Evaluation

Feedback

Due to the lack of interactive engagement among other online students, Some students would want to see more discussion and engagement in the modules through group conversations.

Recommendation

Online students will have more challenging and interesting questions to think about in the weekly forum.

Unit Learning Outcomes
On successful completion of this unit, you will be able to:
  1. Analyse and reflect on key concepts of business analytics
  2. Apply quantitative tools and techniques to analytically identify, examine, investigate and propose solutions to business problems
  3. Synthesise data from a variety of sources and develop models to address practical problems in industry.
Alignment of Learning Outcomes, Assessment and Graduate Attributes
N/A Level
Introductory Level
Intermediate Level
Graduate Level
Professional Level
Advanced Level

Alignment of Assessment Tasks to Learning Outcomes

Assessment Tasks Learning Outcomes
1 2 3
1 - Online Quiz(zes) - 30%
2 - Online Test - 30%
3 - Online Test - 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 and Resources

Textbooks

Prescribed

Business Analytics

4th edition (2020)
Authors: Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann
Cengage Learning
Boston Boston , MA , US
ISBN: 9780357131787
Binding: Paperback

Additional Textbook Information

Textbooks can be accessed online at the CQUniversity Library website. If you prefer your own copy, you can purchase either paper or eBook versions at the CQUni Bookshop here: http://bookshop.cqu.edu.au (search on the Unit code)

IT Resources

You will need access to the following IT resources:
  • CQUniversity Student Email
  • Internet
  • Unit Website (Moodle)
  • Excel spreadsheet software
Referencing Style

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.

Teaching Contacts
Swee Kuik Unit Coordinator
s.kuik@cqu.edu.au
Schedule
Week 1 Begin Date: 06 Mar 2023

Module/Topic

Introduction to Business Analytics

Chapter

Chapter 1 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.

Week 2 Begin Date: 13 Mar 2023

Module/Topic

Descriptive Statistics

Chapter

Chapter 2 Data types and statistics; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Week 3 Begin Date: 20 Mar 2023

Module/Topic

Data Visualisation

Chapter

Chapter 3 Charts and data visualisation; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Assessment 1 Online Quiz (Task A).

The link will open in Week 3 Monday at 9:00 AM (AEST).

Week 4 Begin Date: 27 Mar 2023

Module/Topic

Probability and Modeling Uncertainty

Chapter

Chapter 4 Probability and modelling uncertainty and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Week 5 Begin Date: 03 Apr 2023

Module/Topic

Statistical Inference

Chapter

Chapter 6 Point estimation and hypothesis testing; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Assessment 1 Online Quiz: Task A

Due: Week 5, Friday 11:45PM (AEST)

Vacation Week Begin Date: 10 Apr 2023

Module/Topic

No classes will be held during this week.

Chapter

No classes will be held during this week.

Events and Submissions/Topic

Week 6 Begin Date: 17 Apr 2023

Module/Topic

Regression Analysis

Chapter

Chapter 7 Regression modelling and relationships; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Week 7 Begin Date: 24 Apr 2023

Module/Topic

Decision Analytics

Chapter

Chapter 13 Decision making process and decision analysis; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Assessment 2 Online Test Due: Week 7 Friday (28 Apr 2023) 11:45 pm AEST
Week 8 Begin Date: 01 May 2023

Module/Topic

Optimisation Concept

Chapter

Chapter 10 Building optimisation models; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Week 9 Begin Date: 08 May 2023

Module/Topic

Spreadsheet Models

Chapter

Chapter 10 and 12 Excel spreadsheet models and designs; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Assessment 1 Online Quiz (Task B).

The link will open in Week 9, Monday at 9:00 AM (AEST).


Week 10 Begin Date: 15 May 2023

Module/Topic

Optimisaton and Sensitivity Analysis

Chapter

Chapter 12 Sensitivity analysis and relationships; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Week 11 Begin Date: 22 May 2023

Module/Topic

Forecasting and Time Series

Chapter

Chapter 8 Time series patterns and forecasting accuracy; and Lecture notes and material are available in Moodle

Events and Submissions/Topic

Assessment 1 Online Quiz: Task B 

Due: Week 11, Friday 11:45 PM (AEST)

Week 12 Begin Date: 29 May 2023

Module/Topic

Revision

Chapter

Events and Submissions/Topic

Assessment 3 Online Test Due: Week 12 Friday (2 June 2023) 11:45 pm AEST
Review/Exam Week Begin Date: 05 Jun 2023

Module/Topic

Chapter

Events and Submissions/Topic

Exam Week Begin Date: 12 Jun 2023

Module/Topic

Chapter

Events and Submissions/Topic

Assessment Tasks

1 Online Quiz(zes)

Assessment Title
Online Quiz

Task Description

Assessment 1 comprises two main tasks:

Task A: Online Quiz (Weighted score: 10%) - The quiz includes 20 questions and has a time limit of 30 minutes. It is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and/or propose solutions to business problems from the selected topics in this unit. The quiz will be opened from 9:00 am (AEST) in Week 3, Monday. Please Note: Only one (1) attempt at the quiz will be made. Once you clicked on the quiz link, you must attempt the quiz within 30 minutes. There will be no opportunity to save your answers and return to the quiz at a later time.

Task B: Online Quiz (Weighted score: 20%) - The quiz includes 22 questions and has a time limit of 60 minutes. It is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and/or propose solutions to business problems from the selected topics in this unit. The quiz will be opened from 9:00 am (AEST) in Week 9, Monday. Please Note: Only one (1) attempt at the quiz will be made. Once you clicked on the quiz link then you must attempt the quiz within 60 minutes. There will be no opportunity to save your answers and return to the quiz at a later time.


Number of Quizzes

2


Frequency of Quizzes

Other


Assessment Due Date

The assessments will be due in Weeks 5 (Task A) and 11 (Task B) at 11:45 pm (AEST) (Friday).


Return Date to Students

The results will be available on the unit Moodle site after the quiz due time.


Weighting
30%

Assessment Criteria

Task A: Online Quiz (10 marks) - You will have 30 minutes to complete the online quiz through the Moodle Site.

Task B: Online Quiz (20 marks) - You will have 60 minutes to complete the online quiz through the Moodle Site.


Referencing Style

Submission
Online

Learning Outcomes Assessed
  • 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

2 Online Test

Assessment Title
Assessment 2 Online Test

Task Description

The online test (invigilated assessment) is in the form of an online quiz in Moodle. This assessment is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and propose solutions to business problems from the selected topics in this unit. You are required to answer all questions in the online test (there are no multiple-choice questions in the online test).


Assessment Due Date

Week 7 Friday (28 Apr 2023) 11:45 pm AEST

The online test will be held in Week 7. Further information will be provided on Moodle in Week 5


Return Date to Students

Week 9 Friday (12 May 2023)

Grades and feedback comments are released on the unit Moodle page.


Weighting
30%

Assessment Criteria

Your submission (online test) 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.
  • Accurately suggest and develop the model for detailed analysis in relation to the case study.
  • Able to articulate and evaluate case studies to provide managerial insights and practical limitations based on quantitative outcomes.
  • Clarity of written expression, grammar, and spelling.


Referencing Style

Submission
Online

Submission Instructions
Submissions must be uploaded into Moodle (the unit website) per policy on or before the due date. Penalties apply for late submissions.

Learning Outcomes Assessed
  • 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 Online Test

Assessment Title
Assessment 3 Online Test

Task Description

The online test (invigilated assessment) is in the form of an online quiz in Moodle. This assessment is designed for students to understand key concepts and apply techniques and/or tools to analytically examine and propose solutions to business problems from the selected topics in this unit. You are required to answer all questions in the online test (there are no multiple-choice questions in the online test).


Assessment Due Date

Week 12 Friday (2 June 2023) 11:45 pm AEST

The online test will be held in Week 12. Further information will be provided on Moodle in Week 10.


Return Date to Students

Assessment feedback and grades are to be released upon certification of grades (refer to assessment policy).


Weighting
40%

Assessment Criteria

Your submission (online test) will be assessed according to the following criteria.

  • Demonstrated understanding of the analytical model that is related to the questions posed.
  • Accurately suggest and develop the model for detailed analysis in relation to the applications.
  • Able to articulate and evaluate scenario modelling to provide managerial insights and practical limitations based on quantitative outcomes.
  • Clarity of written expression, grammar, and spelling.


Referencing Style

Submission
Online

Submission Instructions
Submissions must be uploaded into Moodle (the unit website) per policy.

Learning Outcomes Assessed
  • Synthesise data from a variety of sources and develop models to address practical problems in industry.

Academic Integrity Statement

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?