AGRIC 3515WT - Agricultural Experimental Design and Analysis III
Waite Campus - Semester 1 - 2022
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General Course Information
Course Details
Course Code AGRIC 3515WT Course Agricultural Experimental Design and Analysis III Coordinating Unit School of Agriculture, Food and Wine Term Semester 1 Level Undergraduate Location/s Waite Campus Units 3 Contact Up to 7 hours per week Available for Study Abroad and Exchange Y Prerequisites STATS1000, STATS1004, STATS 1504, ECON 1008 or equivalent Assessment Online quizzes, research proposal, research reports, oral/poster presentation Course Staff
Course Coordinator: Dr Kate Delaporte
Course Timetable
The full timetable of all activities for this course can be accessed from .
The course is timetabled on Fridays, 6 contact hours that equate generally to 2hrs of lectures/discussions, 2hrs of tutorials/data collection and 2 hrs of computer practicals. The order and format of activities are flexible, and it is expected that students are attending the whole day.
Consultation hours are negotiated with the class in the first week of the semester. -
Learning Outcomes
Course Learning Outcomes
This course aims to help students see the ‘big picture’ of statistical reasoning in agriculture research, where research is taken in a sense much broader than academic research. Working through the course reader, currently based on the text by a famous statistics presenter Bryan Manly, supported with the working examples and case-studies presented in lectures, and applying the principles to simple hands-on problems in general and agriculturual contexts, working independently and in groups, students will develop:
1 Understanding of principles and typical designs for data collection in sampling and surveys 2 Understanding of principles and typical designs of proper, controlled, experiments 3 Understanding of principles and typical designs of quasi, semi-controlled, experiments 4 Skills in applying this knowledge in practice to research inquiry 5 Skills in designing small-scale research studies and interpreting the results statistically 6 Understanding of the place of statistics in the ethical considerations and overall design of experimentation 7 Good working knowledge of GenStat as the package of choice University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1, 2, 3 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
4, 7 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
5 Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
5 Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
6 Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
2, 3, 4 Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
4, 5 -
Learning Resources
Required Resources
GenStat current release, available on the Waite campus and can be downloaded on personal computers of students enrolled in the course.
‘The design and analysis of research studies’, by Bryan F.J. Manly, Cambridge Press, 2001. The book is available from the 成人大片 Library at Waite, but it is highly recommended that the students acquire their own copy to follow the weekly readings for the course and to use this book as a useful research resource afterwards.
Additional reading and lecture notes are available on MyUni. From 2016, the course reader is also available for download from MyUni.Recommended Resources
To revise the introductory statistics presented in a very relevant manner, the book by Alan G. Clewer and David H. Scarisbrick, Practical Statistics and Experimental Design for Plant and Crop Science, Wiley, 2001, is highly recommended (first five chapters in particular)
Online Learning
MyUni: Teaching materials and course documentation will be posted on the MyUni website ().
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Learning & Teaching Activities
Learning & Teaching Modes
The course is designed to provide students with a broad overview of design and analysis methods for various types of research study. Lectures present the theory, computer tutorials give skills for handling design and analysis in GenStat, and laboratory practicals allow students to design, set up and conduct small-scale studies relevant to the topics discussed in the lectures and demonstrated in the computer practicals
Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
A student enrolled in a 3 unit course, such as this, should expect to spend, on average 12 hours per week on the studies required. This includes both the formal contact time required to the course (e.g., lectures and practicals), as well as non-contact time (e.g., reading and revision).
Learning Activities Summary
To follow the course successfully, students will need to come to the class prepared with their weekly reading tasks.
Learning activities include lectures, computer tutorials for GenStat and problem solving practicals. Every week, all three types of activities are aligned to the common topic.
The course covers the following topics:
Types of research studies in agriculture research in Australia
Sample survey
Spatial sampling
Regression models
Treatment-based experimental designs
Time series designs
Typical randomized designs in agriculture studies
General linear models
Generalized linear models
Computation-intensive statistical inference
Ethical considerations in research study designs
Synthesis: carrying out a research study
An emphasis is placed in the course on the development of students' self-learning and team-working skills. Students are encouraged to work in small groups on research studies designs; the course project is based on group-work.Specific Course Requirements
Attendance of contact hours is highly recommended, as all the activities are important for self-learning and team-working. Attendance will be recorded. Students are advised to contact the course staff in advance, if possible, if they are not able to attend certain days, and take the advantage of one-to-one consultations to discuss the material missing.
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Assessment
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
The assessment is continuing throughout the semester and consists of
individual student reports, a group mini-lecture and a group project report and
presentation. The schedule and weighting of the assessment is given on MyUni
site.
Technical reports assess the student’s ability to design small-scale
research studies of various types and complete the analyses in GenStat.
Mini-lecture assesses the students’ ability to study new material in
statistics with limited supervision and to present the material to the
non-professional audience in a clear and engaging way.
Group project report and presentation assess the students’ ability to
synthesis the material learned in the course and design, conduct and analyse a
small-scale scientific investigation with limited supervision and communicate
the results of the analysis.
Assessment Task Task Type Due Weighting Hurdle Learning Outcome Individual statistical computing reports Formative & Summative 30% No 1-4, 7 Individual workbook solutions Formative & Summative 30% No 1-5 Group mini-lecture Summative 10% No 1-4 Group research project Summative 30% No 1-7
Assessment Related Requirements
It is compulsory to attempt all the assessment. Group assignments will be weighted in accordance to students’ participation and effort. Students have to negotiate themselves the equal load for the group assignments. All individual reports are strictly individual assignments.
Assessment Detail
Statistical computing reports: Six GenStat practical reports will be handed in fortnightly. Prompt written feedback will be provided.
Workbook solutions: Six problem sets will be handed in fortnightly alternating with practical reports. The problem sets will complement the case-study analyses in practical reports. Prompt written feedback will be provided.
Group mini-lecture: Students are expected to come to class having read the material assigned for each week. In this assignment, students will be assessed based on answers to the questions that will form the foundation of class discussion on the sampling strategies and analyses. Peer feedback will be promptly provided.
Design and analysis of a research case-study: Students will design their research study, conduct it and present the design and analysis to the class.
Submission
Submissions of all assignments are strictly on the MyUni site only. Prompt feedback is guaranteed. For formative assignments, students will be given an opportunity to respond to the feedback in writing with the aim of improving their understanding.
Late submission of assessments
Late submissions are not negotiable for the group assignments.If an extension is not applied for, or not granted then a penalty for late submission will apply. Penalty of 10% of the value of the assignment for each calendar day that the assignment is late (i.e. weekends count as 2 days), up to a maximum of 50% of the available marks will be applied. This means that an assignment that is 5 days late or more without an approved extension can only receive a maximum of 50% of the marks available for that assignment.
Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Student Support
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
- Academic Integrity Policy
- Academic Progress by Coursework Students Policy
- Assessment for Coursework Programs Policy
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- Student Experience of Learning and Teaching Policy
- Student Grievance Resolution Process
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