This unit enables students to plan and complete scientific investigations essential to agricultural research. The unit follows a logical progression from understanding the importance of the principles of the scientific method and crafting a well-defined research hypothesis that can be tested using well-designed experiments relevant to agricultural settings and then making sound judgement in the selection of quantitative statistical analyses. Students perform statistical analyses using contemporary statistical software packages and are taught the how to interpret the output and effectively present summarised experimental data sets to a wide range of end users, such as agricultural research and development providers, industry and growers.
|Unit name||Experimental Design and Analysis for Agri-Food Research|
|College/School||College of Sciences and Engineering
Tasmanian Institute of Agriculture
|Discipline||Agriculture and Food Systems|
|Coordinator||Associate Professor Alistair Gracie|
|Available as student elective?||Yes|
|Delivered By||Delivered wholly by the provider|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
* 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 (see withdrawal dates explained 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).
- understand the principles of scientific method and formulate a well-defined research hypothesis
- design experiments relevant to agricultural settings
- make sound judgement in the selection of quantitative scientific methods, apply appropriate statistical analyses, interpret the output and present experimental data sets
- use statistical software packages (e.g. spss) to analyse data sets
- effectively present summarised experimental data sets.
|Field of Education||Commencing Student Contribution 1||Grandfathered Student Contribution 1||Approved Pathway Course Student Contribution 2||Domestic Full Fee|
- Available as a Commonwealth Supported Place
- HECS-HELP is available on this unit, depending on your eligibility3
- FEE-HELP is available on this unit, depending on your eligibility4
1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
3 Please refer here for eligibility for HECS-HELP
4 Please refer here for eligibility for FEE-HELP
Please note: international students should refer to this page to get an indicative course cost.
2 x 50 min lectures per week; 1 x 3 hr practical per week
|Assessment||Data analysis 1 (5%)|Data analysis 2 (5%)|Prac exam (30%)|Examination (40%)|Data analysis 3 (5%)|Prac test (15%)|
|Timetable||View the lecture timetable | View the full unit timetable|
Required readings will be listed in the unit outline prior to the start of classes.
|Links||Booktopia textbook finder|
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