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25841 Analytical Techniques for Decision Making

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2019 is available in the Archives.

UTS: Business
Credit points: 8 cp

Subject level:


Result type: Grade and marks

There are course requisites for this subject. See access conditions.


Advances in information technology have provided organisations access to vast amounts of data. A fundamental challenge facing organisations is how to best make use of this data. This subject is designed to provide students with an understanding of how data can be harnessed to inform decision making, and is presented from the perspective of a business manager. The subject focuses on data-driven decision making through the application and interpretation of analytical techniques and models as well as how the results of data analysis can be communicated effectively to facilitate organisational decision making.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:
1. demonstrate the role of data and data analytics for decision-making in business organisations
2. apply statistical techniques and construct analytical models using spreadsheets and other tools to address business problems
3. critically analyse and evaluate the results of data analyses and analytical models
4. communicate the results of data analyses and analytical models in written and visual forms to support organisational decision-making

Contribution to the development of graduate attributes

This subject contributes to the development of graduate attributes in a number of ways. First, it introduces fundamental concepts relating to data analysis, data management, and data reporting (GA1). Second, students develop analytical skills through the application of quantitative techniques and development of analytical models to address business problems (GA2). Third, students learn how to effectively evaluate and communicate the results of data analysis to managers in written and visual formats (GA3). Finally, students develop their competence in using data-driven decision making processes to formulate recommendations to problems faced by organisations in contemporary practice (GA5).

Teaching and learning strategies

This subject is taught through a blend of seminars, online resources, and self-directed study. Subject content will be presented to students in a variety of formats (lecture slides, notes, videos, articles) and delivered both in-class and online. Students are expected to review materials and complete tasks outside of class before attending. Materials will be provided to students on UTS Online, but students are also expected to seek information independently. This preparation work will enable students to better engage in seminar activities.

Seminars encompass a mix of learning theoretical concepts and developing practical knowledge and skills. Seminars are highly interactive. Students will learn about business analytical techniques and methods and apply these to solve problems and case studies in-class, either individually or in small groups. Students will need to bring a laptop to seminars.

Content (topics)

  • Introduction to data analytics
  • Descriptive, predictive and prescriptive analytical techniques
  • Data management
  • Data visualisation
  • Data reporting


Assessment task 1: In-class assessment 1 (Individual)


This addresses subject learning objective(s):

2 and 3

Groupwork: Individual
Weight: 30%

Assessment task 2: In-class assessment 2 (Individual)


This addresses subject learning objective(s):

2, 3 and 4

Groupwork: Individual
Weight: 35%

Assessment task 3: Assignments (Individual and Group)


30% individual; group 70%


This addresses subject learning objective(s):

1, 2, 3 and 4

Groupwork: Group, group and individually assessed
Weight: 35%

Minimum requirements

To pass the subject, students must achieve at least 50% of the marks allocated to the assessment tasks.

Required texts

Camm, J. D., Cochran, J. J., Fry, M. J., Ohlmann, J. W., Anderson, D. R., & Sweeney, D. J. 2019. Business Analytics, 3rd Edition. Cengage Learning.

ISBN 9781337406420


Black, K., Asafu-Adjaye, J., Burke, P., Perera, N., Sherwood, C., & Wasimi, S. 2018. Business Analytics and Statistics. 1st Edition. Wiley. ISBN: 9780730355434

Evans, J. 2017. Business Analytics, 2nd Edition. Pearson. ISBN: 9781292095448