ECONS205-20B (HAM)

Data Analytics with Business Applications

15 Points

Edit Header Content
Division of Management
School of Accounting, Finance and Economics

Staff

Edit Staff Content

Convenor(s)

Lecturer(s)

Administrator(s)

: denise.martin@waikato.ac.nz
: maria.neal@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: clive.wilkinson@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
Edit Staff Content

Paper Description

Edit Paper Description Content

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. 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.

Edit Paper Description Content

Paper Structure

Edit Paper Structure Content

There will be two hours recorded lecture per week which will be uploaded in Moodle. Additionally, a one-hour Zoom discussion session will be run every week between the students and the lecturer. A two-hour lab will be held each week on campus as well as online. Lab materials are based on lecture contents. In labs, you will be given a set of questions and exercises to complete using Microsoft Excel.

Edit Paper Structure Content

Learning Outcomes

Edit Learning Outcomes Content

Students who successfully complete the course 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
    Linked to the following assessments:
  • 3. Learn modelling uncertainty in business and the use of analytics to real world issues
    Linked to the following assessments:
  • 4. Learn statistical inference and regression analysis
    Linked to the following assessments:
  • 5. Understand and use time series analysis and forecasting
    Linked to the following assessments:
  • 6. Learn to solve optimisation problems in business
    Linked to the following assessments:
  • 7. Demonstrate proficiency in using Microsoft Excel as a statistical and analytical tool
    Linked to the following assessments:
Edit Learning Outcomes Content
Edit Learning Outcomes Content

Assessment

Edit Assessments Content

Assessment Components

Edit Assessments Content

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Online Tests
31 Oct 2020
No set time
20
  • Other: MindTap via Moodle
2. Computer Labs
10
  • In Class: In Lab
3. Midterm Test
18 Aug 2020
9:00 AM
25
  • Online: Submit through Moodle
4. Group Project
3 Nov 2020
No set time
15
  • Presentation: In Lab
5. Final Test
15 Oct 2020
No set time
30
  • Online: Submit through Moodle
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
Edit Assessments Content

Required and Recommended Readings

Edit Required Readings Content

Required Readings

Edit Required Readings Content

Camm, J., Cochran, J., Fry, M., Ohlmann, J., Anderson, D., Sweeney, D., and T. Williams (2020) Business Analytics, 4th edition, Cengage Learning. (3rd edition will also do)

Edit Required Readings Content

Recommended Readings

Edit Recommended Readings Content

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 https://otexts.com/fpp2)

Edit Recommended Readings Content

Other Resources

Edit Other Resources Content

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:

http://fivethirtyeight.com/

https://www.gapminder.org/

Edit Other Resources Content

Online Support

Edit Online Support Content

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

Edit Online Support Content

Workload

Edit Workload Content
As per assessment components and lecture timetable.
Edit Workload Content

Linkages to Other Papers

Edit Linkages Content
Note any linkages to other papers where the linkage is of importance.
Edit Linkages Content

Prerequisite(s)

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

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: ECON204

Edit Linkages Content