Courses & Units

Business Analytics and Operations Research JNB635

Launceston

Introduction

The information era dictates new ways to do business today. Available information through business systems, or social and public media is massive and constantly growing at a very fast rate. Information is nowadays the most precious asset of any initiative. The unit of Business Analytics and Operations Research offers specialists the skills and understanding to use quantitative reasoning skills in business decision making. It is a support tool to managers in solving complex problems in a highly uncertain environment, allows to achieve effectiveness and adequacy of decisions, forecast changes and variability of external and internal processes, and optimise risk levels. Those techniques strongly focus on practical applications, hence there are overlaps with psychology, industrial engineering and organization sciences. Perhaps the best example of this cross-disciplinarity is quantitative decision analysis, also known as mathematics of rationality. It has been developed with the idea to formalise the concept of rationality through quantifiable parameters and make choices based on robust criteria under risk.
This unit provides students with the fundamental and advanced concepts, tools and skills needed to understand the emerging role of business analytics and operations research in organizations. Emphasis would be given to problems in logistics and transport, retailing and procurement. It allows students to understand and apply advanced business analytics tools in a computer-intensive environment and to communicate with analytics professionals to effectively use and interpret analytical models and results for better decision making. There is a descriptive, predictive and prescriptive approaches offered in the unit. Along with this, it discusses the fundamentals and advances of operations research as a discipline area related to simulations and decision-making processes using intelligent methods.
To facilitate your practical activities, the selected textbook includes the online platform MindTap – it is a development of Cengage that provides engaging content, challenges every individual and builds student confidence. You may find more information about the platform (also available as mobile app) at https://www.cengage.com/mindtap/. Most exercises require calculations with the use of computers, calculators or other computational tools. Having said this, what you really need to learn are the methods rather than the calculation skills. While some may find this unit challenging, its knowledge is essential to understand the fundamentals of decision making in complex business environment.

Summary

Unit name Business Analytics and Operations Research
Unit code JNB635
Credit points 12.5
College/School College of Sciences and Engineering
Australian Maritime College
Discipline Maritime and Logistics Management
Coordinator Professor Nataliya Nikolova
Available as student elective? No
Delivered By University of Tasmania

Availability

Location Study period Attendance options Available to
Launceston Semester 2 On-Campus Off-Campus International International Domestic Domestic

Key

On-campus
Off-Campus
International students
Domestic students
Note

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Key Dates

Study Period Start date Census date WW date End date
Semester 2 11/7/2022 9/8/2022 29/8/2022 16/10/2022

* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (see withdrawal dates explained for more information).

Unit census dates currently displaying for 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

Learning Outcomes

  • Develop and apply advanced skills to collect, analyse and interpret information specific to decisions in logistics management
  • Use intelligent techniques for knowledge discovery to solve real-life decision problems in logistics management
  • Assess different business analytics solutions and their applicability to the decision making process arising in diverse contexts
  • Define and justify practical decision recommendations based on supporting evidence, critical thinking and professional judgment
Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
020105 $1,002.00 $1,002.00 not applicable $2,402.00
  • Available as a Commonwealth Supported Place
  • HECS-HELP is available on this unit, depending on your eligibility3
  • FEE-HELP is available on this unit, depending on your eligibility4

1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
3 Please refer here for eligibility for HECS-HELP
4 Please refer here for eligibility for FEE-HELP

If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.

Please note: international students should refer to this page to get an indicative course cost.

Requisites

Mutual Exclusions

You cannot enrol in this unit as well as the following:

JNB535

Teaching

Assessment (15%)| (15%)| (30%)| (40%)
TimetableView the lecture timetable | View the full unit timetable

Textbooks

Required

Camm, JD, Cochran, JJ, Fry, MJ, Ohlmann, Business Analytics, 4th edition, Cengage, 2021

This textbook is available to purchase from the link below:

https://au.cengage.com/c/business-analytics-4e-camm/9780357131787/

Recommended

Press, W, Teukolski, S, Vetterling, WT & Flannery, B 2007, Numerical recipes: the art of scientific computing, 3rd edn, Cambridge University Press.

Efron, B. & Tibshirani, RJ, An introduction to the bootstrap, CRC Press, 1994

Camm, JD, Cochran, JJ, Fry, MJ, Ohlmann, D. Anderson, Business Analytics, 3rd edition, Cengage, 2019

French, Simon & David Rios Insua. 2010. Statistical decision theory: Kendall's library of statistics 9. Chichester, UK: John Wiley & Sons Ltd.

Viertl, R. Statistical methods for fuzzy data. John Wiley. UK, 2011

Selvanathan, SA, Selvanathan, S & Keller, G 2017, Business statistics: Australia New Zealand, Seventh Edition+ MindTap Printed Access Card (two items supplied in a value pack), Cengage Learning Australia, ISBN: 9780170285827

Lind, DA, Marchal, WG & Wathen, SA 2017, Statistical techniques in business & economics, 17th edn, Irwin McGraw-Hill, New York

Albright, SC, Winston, WL & Zappe, C 2011, Data analysis & decision making, 4th edn, South-Western Cengage Learning, Mason, OH.

Anderson, DR, Sweeney, DJ, Williams, TA, Camm, JD & Martin, K 2013, Quantitative methods for business, 12th edn, South-Western Cengage Learning, Mason, OH.

Berenson, ML, Levin, DM, Krehbiel, TC, Watson, J, Jayne, N & Turner, L 2013, Basic business statistics – concepts and applications, 3rd edn, Person Australia Group, Frenchs Forest.

Hillier, FS & Hillier, MS 2014, Introduction to management science: A modelling and case studies approach with spreadsheets, 5th edn, McGraw-Hill Irwin, New York.

Oakshott, L 2012, Essential quantitative methods for business, management and finance, 5th edn, Palgrave Macmillan, Hampshire.

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