ECONS205-21B (HAM)

Data Analytics with Business Applications

15 Points

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Division of Management
School of Accounting, Finance and Economics


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Paper Description

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Business analytics offers a unique approach to learn how to make >. This course covers the analytical and statistical techniques that business and management students are most likely to use in their future courses and professional careers. Students will learn different types of data analytics methods and their applications to problems in accounting, economics, finance, marketing, and business in general.

This course uses a combination of lectures, lab sessions, and online discussions in Moodle forum. Students will have hands-on work with data and Microsoft Excel. Weekly computer-based workshops aim to enhance understanding of how the techniques introduced in lectures apply in a business context. Topics to be covered include presenting data using visual and descriptive statistics, measuring and understanding the relationship between variables, predictive analytics and prescriptive analytics tools. Examples from economics, finance, accounting, managerial decision making, supply chain & logistics and marketing will illustrate the material covered. Emphasis will be placed on understanding concepts and analysis of data. The paper will also provide opportunities for students to enhance their teamwork and communication through a group project.

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Paper Structure

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Lecture and office hour:

There will be three hours of lecture each week which will be also available in panopto recording and uploaded in Moodle. In addition, the paper convenor will hold a one hour office hour per week and the time will be announced in Moodle. You can make an appointment to see the convenor any other time.


A two-hour lab will be held each week on campus. There will be two labs each week which are three-hour sessions for those students who need extra time to catch up. Lab materials are based on lecture contents. You will be given a set of questions and exercises to complete in the lab using Microsoft Excel and then hand in a hard copy to the tutors. Your lab marks depend on whether you submitted the hard copy in the lab session.


There will be six drop-in sessions held by both the lecturer and the tutors during the whole term. Three sessions will be held before the teaching recess and three afterwards. The drop-in sessions will take place within the campus and the time and venue will be informed during the term via Moodle. It is not compulsory but you are requested to RSVP in Moodle so that we may book an appropriate size room.

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Learning Outcomes

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Students who successfully complete the paper should be able to:

  • 1. Interpret business and economic data
    Linked to the following assessments:
  • 2. Understand how business analytics helps mangers to undertake informed decision making
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  • 3. Learn modelling uncertainty in business and the use of analytics to real world issues
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  • 4. Learn statistical inference and regression analysis
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  • 5. Understand and use time series analysis and forecasting
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  • 6. Learn to solve optimisation problems in business
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  • 7. Demonstrate proficiency in using Microsoft Excel as a statistical and analytical tool
    Linked to the following assessments:
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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 67:33. There is no final exam. The final exam makes up 33% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 67:33 or 0:0, whichever is more favourable for the student. The final exam makes up either 33% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Online Tests
15 Oct 2021
No set time
  • Other: MindTap via Moodle
2. Computer Labs
  • Hand-in: In Lab
3. Midterm Test
17 Aug 2021
10:00 AM
  • In Class: In Lecture
4. Group Project
  • Online: Submit through Moodle
5. Spot Quiz
  • In Class: In Lecture
6. Exam
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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Camm, J., Cochran, J., Fry, M., Ohlmann, J., Anderson, D., Sweeney, D., and T. Williams (2020) Business Analytics, 4th edition, Cengage Learning. (

earlier edition will also be suitable and it is available on course reserve at the library )
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Recommended Readings

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Duignan, J. (2014) Quantitative Methods for Business Research Using Microsot Excel, Cengage Learning (On Course Reserve)

Koop, G (2013) Analysis of Economic Data, Wiley (on Course Reserve)

Hyndman, R. and Athanasopoulos, G. (2018) Forecasting: Principles and Practice, 2nd ed., OTexts: Melbourne, Australia (freely available online at

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Other Resources

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University of Waikato Student Learning: Maths & Stats Resources

In addition to the required textbook, students are encouraged to read widely including the business section of newspaper, the Economist magazine, and other similar sources. Additional paper resources will be made available on Moodle.

The following websites are examples of Data Analytics being used in practice:

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Online Support

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All course materials, plus other information of importance to students are available if via Moodle.

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As per assessment components and lecture timetable.
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Linkages to Other Papers

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Prerequisite papers: 15 points from any ECONS, ACCTN, FINAN or STATS 100 level papers.




Restricted papers: ECON204, BUSAN205

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