BUSAN205-23B (TGA)

Data Analytics with Business Applications

15 Points

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The University of Waikato
Academic Divisions
Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Lecturer(s)

Administrator(s)

: denise.martin@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: em.pooley@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.
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What this paper is about

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This course aims to equip you with an understanding of the key concepts, techniques, and applications of business analytics. In particular, we focus on the analytical and statistical techniques that business and management students will most likely 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, problem sets and student presentations. Students will get hands-on experience working with data in Microsoft Excel. Weekly computer-based exercises 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. The paper will also provide opportunities for students to enhance their teamwork and communication skills with an empirical group research project and poster presentation.

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How this paper will be taught

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This paper will be taught using lectures (3 hours), and via self-paced exercises (with support available on-campus labs or via Zoom).

In lectures, we will carefully develop the basic ideas and tools and provide some examples of the way they can be used. The exercises provide an opportunity for students to apply these ideas and tools.

Note: BUSAN205-23A (TGA) is offered in Flexi Synchronous Mode, which means on-campus activities (lectures, labs) are available for students to attend in person. Students, however, can complete the paper online if they choose. For those taking the paper online you are required to engage in activities, such as tests, at certain times.

Labs

Lab sessions are a chance for you to get help with your weekly self-paced exercises.

Lab sessions commence in the second week of the semester. For students unfamiliar with Excel there will be a lab in the first week on Excel basics. Details of this lab will be advised, via Moodle, before lectures start

Students may select a lab session by clicking on "Group Selection" in Moodle. Depending on enrolment numbers, some lab times that are listed on the online timetable may not be available. The Friday 10am lab will be the online lab.

Alternative lab arrangements will be made for Kingitanga day (Thursday 14 September). These will be discussed in class.

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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 (2019) Business Analytics, 3rd edition, Cengage Learning.

This is available online through the University library. A physical copy is available at the Tauranga campus library.

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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Interpret business and economic data
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  • Explain how data analytics theory applies to business decision making
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  • Identify and apply appropriate data analytics methods to real world business issues and interpret the results, including analysis of random experiments and methods of comparing groups
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  • Make inference on population means, difference between means for business decision making
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  • Use regression analysis and critically appraise the merits and shortcomings of using regression methods to analyse empirical data
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  • Evaluate evidence to inform decision making
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  • Demonstrate proficiency in using Microsoft Excel as a statistical and analytical tool
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Assessments

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How you will be assessed

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PLEASE NOTE THIS COURSE IS 100% INTERNALLY ASSESSED. The 70:30 split noted elsewhere on this course outline (as at 30 June 2023) is in the process of being amended, but this needs to be signed off by various parties.
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The internal assessment/exam ratio (as stated in the University Calendar) is 70:30. There is no final exam. The final exam makes up 30% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 70:30 or 0:0, whichever is more favourable for the student. The final exam makes up either 30% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Midterm Test
6 Sep 2023
4:00 PM
25
  • Online: Submit through Moodle
2. Submitted Computer Exercises
15
  • Online: Submit through Moodle
3. Group Empirical Project and Presentation
2 Oct 2023
5:00 PM
23
  • Presentation: In Class
4. Quizzes
7
  • Online: Submit through Moodle
5. Final test
18 Oct 2023
4:00 PM
30
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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