CORPFIN 2503 - Business Data Analytics
North Terrace Campus - Semester 2 - 2020
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General Course Information
Course Details
Course Code CORPFIN 2503 Course Business Data Analytics Coordinating Unit Adelaide Business School Term Semester 2 Level Undergraduate Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Prerequisites ECON 1008 Assessment Mid-term test, group assignment and final examination Course Staff
Course Coordinator: Associate Professor Sigitas Karpavicius
Course Timetable
The full timetable of all activities for this course can be accessed from Course Planner.
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Learning Outcomes
Course Learning Outcomes
On successful completion of this course, students will be able to:
1. Collect the data from proprietary (e.g., Refinitiv Eikon) and public sources
2. Process the data and prepare it for further analysis
3. Apply advanced quantitative and qualitative modelling techniques using SAS® and NVIVO® software
4. Critically interpret the obtained quantitative and qualitative results.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) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
1-4 Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1-4 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
1-4 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
1-4 Intercultural and ethical competency
- adept at operating in other cultures
- comfortable with different nationalities and social contexts
- able to determine and contribute to desirable social outcomes
- demonstrated by study abroad or with an understanding of indigenous knowledges
1-4 Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
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Learning Resources
Required Resources
Text book: Konasani, V. R. and Kadre, S. (2015). ‘Practical Business Analytics Using SAS: A Hands-on Guide’ (a free electronic copy is available from the library).
Computer: Students will need a computer with ‘SAS® University Edition’ (can be downloaded for free from www.sas.com) and ‘NVIVO®’ (a free licence can be obtained from the University’s website) installed. -
Learning & Teaching Activities
Learning & Teaching Modes
The approach in this course is to first establish the basic knowledge of analytical tools (e.g., SAS® software) and then to build upon these to analyse real-world issues. This will be done through lectures, tutorials, assignment, mid-term test, and examination.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements. The University expects full-time students (i.e. those taking 12 units per semester) to devote a total of 48 hours per week to their studies. This means that you are expected to commit approximately 9 hours for a three-unit course or 13 hours for a four-unit course, of private study outside of your regular classes. Students in this course are expected to attend all lectures throughout the semester plus one tutorial class each week.Learning Activities Summary
Week
Topic
Required reading*
Learning activities
1
Introduction to data analytics and data handling
Ch. 1, 2, 3, 4
Lecture and workshop activities
2
Visual analytics and data mining
Ch. 5
Lecture and workshop activities
3
Descriptive statistics and data exploration
Ch. 6, 7, 8
Lecture and workshop activities
4
Applications of linear regressions
Ch. 9, 10
Lecture and workshop activities
5
Applications of logit and probit models
Ch. 11
Lecture and workshop activities
6
Applications of other discrete models
TBA
Lecture and workshop activities
7
Mid-term test
8
Monte-Carlo simulations
TBA
Lecture and workshop activities
9
Time-series analysis
Ch. 12 (pp. 441-465)
Lecture and workshop activities
10
Forecasting
Ch. 12 (pp. 465-507)
Lecture and workshop activities
11
Text analytics
Xiang et al. (2015)
Lecture and workshop activities
12
Big data
Ch. 13
Lecture and workshop activities
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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 Weighting Quizzes 10% Mid-term test 20% Group Assignment 20% Final Examination 50% Assessment Detail
The assessment components are as follows:
1) Quizzes (mostly, on a weekly basis) will be conducted via MyUni.
2) There will be a mid-semester test held in Week 7. The test will be conducted via MyUni. Further details will be announced on MyUni.
3) Group assignment involves analysing contemporaneous business problems using advanced statistical methods and software.
4) Final/Replacement Exam (during examination schedule).
To gain a pass for this course, a mark of at least 50% overall needs to be obtained.Submission
Further details will be provided on MyUni.
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 Access Adelaide.
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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
- International Student Support
- Library Services for Students
- LinkedIn Learning
- Student Life Counselling Support - Personal counselling for issues affecting study
- Students with a Disability - Alternative academic arrangements
- YouX Student Care - Advocacy, confidential counselling, welfare support and advice
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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
- Elder Conservatorium of Music Noise Management Plan
- 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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