Courses & Units
Data and Analysis ZAB114
Introduction
In this unit, you will be introduced to mathematical and statistical methods for analysing scientific, business or technical data to inform and support decision-making. You will explore why data is needed and how it is used to make decisions, including how data are collected, analysed, interpreted and presented, and you will learn and apply a suite of common statistical and mathematical methods to generate evidence for decision-making. You will also be introduced to data management software and learn how to represent and communicate mathematical and statistical information effectively. Through case studies relevant to your discipline, you will learn how to problem solve, generate evidence, and present solutions using data handling and statistical approaches.
This unit also incorporates learning through practice by exposing you to authentic learning experiences. These experiences are placed at the centre of learning and assessment, for you to develop the skills, knowledge and behaviours necessary to respond to industry, community and/or global needs.
You will be introduced to:
- a range of methods, tools, techniques and approaches to practice
- principles and perspectives such as values, ethics, empathy and leadership in real world scenarios
- reflection and deliberative thinking as a means of developing knowledge, skills, attitudes and aspirations
- ways of understanding problems and developing solutions through active inquiry
Summary
| Unit name | Data and Analysis |
|---|---|
| Unit code | ZAB114 |
| Credit points | 12.5 |
| College/School | College of Business & Economics University College |
| Discipline | Agribusiness |
| Coordinator | Doctor Suzie Jones |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
Availability
This unit is currently unavailable.
* 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 (refer to How do I withdraw from a unit? 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).
Learning Outcomes
- Describe how data are handled and analysed to support decision making in business, science, and technology disciplines
- Select and apply data analysis and presentation methods to generate evidence that supports decision-making
- Interpret and communicate evidence generated from mathematical and statistical approaches
- Critically reflect on own technical practice and discipline knowledge to generate plans for self-development
Fee Information
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| not applicable |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on 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 What is an indicative Fee? to get an indicative course cost.
Requisites
Mutual Exclusions
You cannot enrol in this unit as well as the following:
ZAB103|ZAS103|ZAS113Teaching
| Teaching Pattern | Weekly online tutorials, 3 x online half-day workshops per semester |
|---|---|
| Assessment | AT2: Report: Data Analysis (35%)|AT1: Exploring Data as Evidence (20%)|AT3: Presentation: Communicating Data for Decision Making, with Peer Feedback (45%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
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