An investigation of a business problem (real or simulated), backed by appropriate applied and academic literature.
This paper is designed in conjunction with the Master of Business Data Science and allows the student to independently develop and extend their skills in Data Science and Data Analytics. This may involve solving some data modelling concepts with an external agency or within a setting directed by an academic staff member.
|Paper title||Applied Project|
|Teaching period||1st Non standard period (25 February 2019 - 20 February 2020)|
|Domestic Tuition Fees (NZD)||$2,614.74|
|International Tuition Fees (NZD)||$11,032.23|
- Limited to
- Limited to: MBusDataSc
- Teaching staff
- Dr Peter A. Whigham
- "An Introduction to Statistical Learning", by G.James, D. Witten, T. Hastie & R. Tibshirani. This is available online through the Otago Library.
- Graduate Attributes Emphasised
- Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship,
Communication, Critical thinking, Cultural understanding, Ethics, Information literacy,
View more information about Otago's graduate attributes.
- Learning Outcomes
- Plan and conduct an independent (applied) project that will be relevant and useful to the chosen business context
- Apply critical thinking skills and interdisciplinary approaches to an in-depth analysis of the chosen business problem
- Demonstrate problem-solving abilities in a multicultural global business environment
- Work independently to produce a report with a high level of communication skills (verbal and written)
- Paper Structure
The paper runs from the beginning of first semester, with the final thesis submission in mid-February of the next calendar year. The course will provided an introduction to writing a thesis, present a range of possible research topics, and support the students throughout the year to complete a solid technical and academic research project.