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BMBA71-301: Data Analytics for Decision Making May 2020 [Standard]

General information

This subject develops the student’s facility for evidence-based decision making, by introducing students to the use and application of data. As the business world has increasing access to data, and in the availability of big data sets which allow greater understanding of customers and other business related data, effective use of the data will enable decisions to become more informed. This subject will consider the role of data in an evolving business system, discuss and review common sources of data and processes for developing superior data sets, and will introduce the quantitative methods that are needed for understanding what the data tells us re the decision we need to make. It develops an understanding of modern computational methods to solve quantitative problems in business decision making, using a case-based approach to using data.

Details

Academic unit:Bond Business School
Subject code:BMBA71-301
Subject title:Data Analytics for Decision Making
Subject level:Postgraduate
Semester/Year:May 2020
Credit points:10

Delivery & attendance

Timetable: https://bond.edu.au/timetable
Delivery mode:

Standard

Workload items:
  • Seminar: x12 (Total hours: 24) - Seminar 1
  • Seminar: x12 (Total hours: 24) - Seminar 2
  • Personal Study Hours: x12 (Total hours: 72) - Study time and reviewing materials
Attendance and learning activities: Attendance at all class sessions is expected. Students are expected to notify the instructor of any absences with as much advance notice as possible.

Resources

Prescribed resources: No Prescribed resources. After enrolment, students can check the Books and Tools area in iLearn for the full Resource List.
[email protected] & Email:[email protected] is the online learning environment at Bond University and is used to provide access to subject materials, lecture recordings and detailed subject information regarding the subject curriculum, assessment and timing. Both iLearn and the Student Email facility are used to provide important subject notifications. Additionally, official correspondence from the University will be forwarded to students’ Bond email account and must be monitored by the student.

To access these services, log on to the Student Portal from the Bond University website as www.bond.edu.au

Enrolment requirements

Requisites: ?

Nil

Restrictions: ?

Nil

Assurance of learning

Assurance of Learning means that universities take responsibility for creating, monitoring and updating curriculum, teaching and assessment so that students graduate with the knowledge, skills and attributes they need for employability and/or further study.

At Bond University, we carefully develop subject and program outcomes to ensure that student learning in each subject contributes to the whole student experience. Students are encouraged to carefully read and consider subject and program outcomes as combined elements.

Program Learning Outcomes (PLOs)

Program Learning Outcomes provide a broad and measurable set of standards that incorporate a range of knowledge and skills that will be achieved on completion of the program. If you are undertaking this subject as part of a degree program, you should refer to the relevant degree program outcomes and graduate attributes as they relate to this subject.

Find your program

Subject Learning Outcomes (SLOs)

On successful completion of this subject the learner will be able to:
  1. Understand the role of data in evidence based decision making
  2. Examine the systems by which data is or can be made available
  3. Possess an understanding of measurement issues and processes for understanding relationships based on statistical theory
  4. Apply modern quantitative tools (Microsoft Excel) to data analysis in a business context
  5. Analyse and interpret data to provide meaningful information to assist in decision making

Assessment

Assessment details

TypeTask%Timing*Outcomes assessed
Online Quiz Minor Projects/Quizzes 20% Progressive 1, 2, 3, 4, 5.
Case Analysis Project 30% Week 11 1, 2, 3, 4, 5.
Computer-Aided Examination (Open) Final Examination/Project 50% Final Examination Period 1, 2, 3, 4, 5.
  • * Assessment timing is indicative of the week that the assessment is due or begins (where conducted over multiple weeks), and is based on the standard University academic calendar
  • C = Students must reach a level of competency to successfully complete this assessment.

Assessment criteria

High Distinction 85-100 Outstanding or exemplary performance in the following areas: interpretative ability; intellectual initiative in response to questions; mastery of the skills required by the subject, general levels of knowledge and analytic ability or clear thinking.
Distinction 75-84 Usually awarded to students whose performance goes well beyond the minimum requirements set for tasks required in assessment, and who perform well in most of the above areas.
Credit 65-74 Usually awarded to students whose performance is considered to go beyond the minimum requirements for work set for assessment. Assessable work is typically characterised by a strong performance in some of the capacities listed above.
Pass 50-64 Usually awarded to students whose performance meets the requirements set for work provided for assessment.
Fail 0-49 Usually awarded to students whose performance is not considered to meet the minimum requirements set for particular tasks. The fail grade may be a result of insufficient preparation, of inattention to assignment guidelines or lack of academic ability. A frequent cause of failure is lack of attention to subject or assignment guidelines.

Quality assurance

For the purposes of quality assurance, Bond University conducts an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.

Study information

Submission procedures

Students must check the [email protected] subject site for detailed assessment information and submission procedures.

Policy on late submission and extensions

Unexplained late submissions will not be considered for marks. Penalties will apply for late submissions. The specific late penalties for the exams appear below. Policy for Final Exams: Penalty of 25% per 15 minutes late (rounded up), such that exams submitted more than 45 minutes late receive an ungraded zero.

Policy on plagiarism

University’s Academic Integrity Policy defines plagiarism as the act of misrepresenting as one’s own original work: another’s ideas, interpretations, words, or creative works; and/or one’s own previous ideas, interpretations, words, or creative work without acknowledging that it was used previously (i.e., self-plagiarism). The University considers the act of plagiarising to be a breach of the Student Conduct Code and, therefore, subject to the Discipline Regulations which provide for a range of penalties including the reduction of marks or grades, fines and suspension from the University.

Bond University utilises Originality Reporting software to inform academic integrity.

Feedback on assessment

Feedback on assessment will be provided to students within two weeks of the assessment submission due date, as per the Assessment Policy.

Disability support

If you have a disability, illness, injury or health condition that impacts your capacity to complete studies, exams or assessment tasks, it is important you let us know your special requirements, early in the semester. Students will need to make an application for support and submit it with recent, comprehensive documentation at an appointment with a Disability Officer. Students with a disability are encouraged to contact the Disability Office at the earliest possible time, to meet staff and learn about the services available to meet your specific needs. Please note that late notification or failure to disclose your disability can be to your disadvantage as the University cannot guarantee support under such circumstances.

Additional subject information

As part of the requirements for Business School quality accreditation, the Bond Business School employs an evaluation process to measure and document student assessment as evidence of the extent to which program and subject learning outcomes are achieved. Some examples of student work will be retained for potential research and quality auditing purposes only. Any student work used will be treated confidentially and no student grades will be affected.

Subject curriculum

What are data analytics and big data, the role of data analytics, descriptive statistics (graphical and numerical) and the role of ethics?

Usefulness of probability concepts in business, basics of probability, discrete random variables, expectation, variance

1, 2, 3, 4, 5.

Continuous random variables, normal distribution

1, 2, 3, 4, 5.

Types of data, sampling techniques, distribution of the sampling mean

1, 2, 3, 4, 5.

Confidence intervals for the mean, hypothesis testing for the mean

1, 2, 3, 4, 5.

Simple and Multiple Linear Regression - introduction to the theory and application

1, 2, 3, 4, 5.

Linear Probability Model and Logistic Regression

1, 2, 3, 4, 5.

Big Data classification techniques

1, 2, 3, 4, 5.

Big Data clustering techniques

1, 2, 3, 4, 5.

How to evaluate big data projects as managers

1, 2, 3, 4, 5.
Approved on: Apr 28, 2020. Edition: 1.1