ECONS205-18B (HAM)
Data Analytics with Business Applications
15 Points
Staff
Convenor(s)
John Gibson
4289
MSB.2.15
Thursday 1-2 pm
john.gibson@waikato.ac.nz
|
Susan Olivia
4112
MSB.2.11
Thursdays 3-5pm or by appointment
susan.olivia@waikato.ac.nz
|
Administrator(s)
Tutor(s)
Librarian(s)
You can contact staff by:
- Calling +64 7 838 4466 select option 1, then enter the extension.
-
Extensions starting with 4, 5 or 9 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.
Paper Description
The exponential growth in the availability of data requires that students are able to make informed decisions using data, and effectively communicate their data analyses.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, case discussions, lab sessions and student presentations. 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. Empirical examples from economics, finance, accounting, 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 skills with an empirical group research project and poster presentation.
Paper Structure
Learning Outcomes
Students who successfully complete the course should be able to:
Assessment
Assessment Components
The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam.
Required and Recommended Readings
Required Readings
Camm, J., Cochran, J., Fry, M., Ohlmann, J., Anderson, D., Sweeney, D., and T. Williams (2019) Business Analytics, 3rd edition, Cengage Learning.
Recommended Readings
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)
Other Resources
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:
Online Support
All course materials, plus other information of importance to students are available if via Moodle.
Workload
Linkages to Other Papers
Prerequisite(s)
Prerequisite papers: Two from (ACCTN101 or ACCT101), (ECONS101 or ECON100) or FINAN101; or 14 credits at NCEA Level 3 across any two of maths or statistics or calculas.
Restriction(s)
Restricted papers: ECON204