BUSANA 7004 - Business Analytics for Managers
North Terrace Campus - Trimester 2 - 2023
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General Course Information
Course Details
Course Code BUSANA 7004 Course Business Analytics for Managers Coordinating Unit Adelaide Business School Term Trimester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Course Staff
Course Coordinator: Professor Ralf Zurbrugg
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
On successful completion of this course students will be able to:
1 Utilise basic statistical theory to represent and solve business data problems. 2 Construct and test hypotheses. 3 Understand where and how both structured and unstructured data can be used to provide business solutions. 4 Be competent at extracting business data and representing it in a meaningful manner. University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1,2,3,4 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
3,4 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
3,4 Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
4 Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
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Learning Resources
Required Resources
This course uses a number of resources. A reference text is also recommended to students in the class with details made available in the course webpages. -
Learning & Teaching Activities
Learning & Teaching Modes
In this course a mix of learning methods, including topic presentations, interactive discussion, the solving of assigned questions and problems, and sharing of business experiences and observation is used.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
Three intensive classes are spread across three months, with each intensive consisting of 12 hours of teaching. Students should allocate up to eight hours per week of study time to do appropriate readings, solving set questions, problems, and assignments in addition to attendance at scheduled class sessions.Learning Activities Summary
Module 1 - The Value of Data Science
Module 2 - The Data Pipeline and Ethics
Module 3 - Descriptive and Visual Analytics
Module 4 - Data Wrangling
Module 5 - Statistical Inference
Module 6 - Supervised Learning
Module 7 - Unsupervised Learning
Module 8 - Deep Learning
Specific Course Requirements
Access to a laptop and also Microsoft Excel.
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Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Assessment Task Task Type Due Date Course Learning Outcome(s) being assessed Assessment
WeightingHomework Formative and Summative Throughout the teaching period with deadlines set for each piece of work a day before the following teaching session.
1,2,3 30% Research Assignment Summative Two weeks following the last class 1,2,3, 4 40% Online Test Summative One week following the last class 1,2,3 30% Assessment Detail
Homework: Short exercises, mostly done online, to reinforce the content taught in the different teaching sessions.
Research Assignment: Students choose a business-analytics project that suits their interests and are required to deliver a formal report.
Online Test: Summative test where students are given data and must provide answers to a set of questions.Submission
All submissions occur online either through the course's MyUni webpages or through the course textbook publisher's education gateway.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Student Support
- Academic Integrity for Students
- Academic Support with Maths
- Academic Support with writing and study skills
- Careers Services
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
- Copyright Compliance Policy
- Coursework Academic Programs Policy
- Intellectual Property Policy
- IT Acceptable Use and Security Policy
- Modified Arrangements for Coursework Assessment Policy
- Reasonable Adjustments to Learning, Teaching & Assessment for Students with a Disability Policy
- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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Fraud Awareness
Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.
The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.
