ANIML SC 2520RW - Research Methodology for Animal Sciences II

Roseworthy Campus - Semester 1 - 2015

This course is concerned with understanding and application of, the scientific method in biological research, and in particular, the animal sciences. The course has a foundation in the philosophy of science. Particular emphasis is given to the application of statistical hypothesis testing, which is explored in a series of case studies. In addition, research skills in proposal preparation, project management, teamwork, presentations skills and publication writing are developed in the context of scientific research.

  • General Course Information
    Course Details
    Course Code ANIML SC 2520RW
    Course Research Methodology for Animal Sciences II
    Coordinating Unit School of Animal and Veterinary Sciences
    Term Semester 1
    Level Undergraduate
    Location/s Roseworthy Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites STATS 1000 or STATS 1004
    Incompatible BIOMET 2500RW, BIOMET 2500WT
    Course Description This course is concerned with understanding and application of, the scientific method in biological research, and in particular, the animal sciences. The course has a foundation in the philosophy of science. Particular emphasis is given to the application of statistical hypothesis testing, which is explored in a series of case studies. In addition, research skills in proposal preparation, project management, teamwork, presentations skills and publication writing are developed in the context of scientific research.
    Course Staff

    Course Coordinator: Dr Michelle Hebart

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    1 The anticipated knowledge, skills and/or attitude to be developed by the student are:
    2 Ability to develop scientific hypotheses
    3 Understanding of the principles & practices of experimental designAbility to use selected statistical methods: correlation, regression (simple linear, polynomial, multiple linear), general linear models (with interactions), analysis of categorical variables (contingency tables)
    4 Ability to perform project management in the context of planning and executing a research project
    5 Demonstrate effective written, oral and graphical presentation skills
    6 Ability to work in small groups to design, conduct, and analyse an experiment
    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)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1, 2, 3
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1, 3, 6
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 3, 4, 6
    Skills of a high order in interpersonal understanding, teamwork and communication. 5, 6
    A proficiency in the appropriate use of contemporary technologies. 2, 3
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 1, 3, 4
    A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 4, 6
  • Learning Resources
    Required Resources
    There is no required text book for this course. Sources used for all learning activities will be referenced and students are encouraged to not only rely on the notes given to them, but also to read more widely using these references as a starting point.
    Online Learning
    MyUni: Teaching materials and course documentation will be posted on the MyUni website (
  • Learning & Teaching Activities
    Learning & Teaching Modes
    This course will be delivered by the following means:
    2 x 1hr lectures per week
    2 x 1hr computer practical sessions per week
    1 x 2hr tutorials per week
    Students will receive lecture and tutorial notes online.

    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
    Week 1 Introduction
    Develop a Research Question
    Week 2 Design a Research Project
    Produce and present a research proposal for funding
    Week 3 Experimental Design and Power
    Specific Designs
    Week 4 Specific Designs
    Week 5
    Messages from Commercial Un-Replicated Data Sets
    Week 6 Manage, Summarise and Present Data
    Explore Data & Test Hypotheses
    Week 7 Analyse Data
    Week 8 Assumptions
    Interpreting Data, and Mathematical Techniques
    Week 9 Interpret data, Understanding Interactions
    Report and Discuss Results
    Week 10 Produce a Final Report/Paper
    Validating Models
    Week 11 Qualitative Research
    Week 12 Non-Parametric Models
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    Assessment Task Type of assessment Percentage of total assessment for grading purposes Hurdle
    Outcomes being assessed
    Tutorial assessment Formative


    Yes 2,3,5
    Practical assessments Summative 10% 1,2,3,5
    Assignments Summative 40% 1-6
    Theory exam Summative 45% Yes 1,2,3
    Assessment Related Requirements

    Attendance at practicals and tutorials is compulsory. Students are able to apply for an allowed absence from a class by submitting the application form, with appropriate supporting documentation, to the Course Co-ordinator. Application forms can be downloaded from

    To pass this course students require both
    A minimum of 40% for the Exam AND
    A minimum of 40% for the combined non-Exam component (i.e. at least 22 out of 55)

    Students that do not attain either or both of these minimum requirements will be provided with additional assessment, in the form of an additional examination and/or an additional statistical analysis assessment.

    Assessment Detail
    Tutorials (5%): Tutorial mark is based on individual contribution to each session during the semester. This may include short quizzes that the students are able to use for formative assessment to determine their current levels of understanding of concepts.

    Practicals (10%): four (4) assessments are to be submitted throughout the semester. These are submitted at the beginning of the next practical session.

    Assignments (40% total): three (3) assignments are to be submitted, worth 15%, 15% and 10% of the final assessment, respectively. A presentation will be required for the first assignment.

    Theory Exam (45%): Students will be allowed to take calculators and one (1) A4 page with writing on both sides into the exam.
    Extensions for Assessment Tasks
    Extensions of deadlines for assessment tasks may be allowed for reasonable causes. Such situations would include compassionate and medical grounds of the severity that would justify the awarding of a supplementary examination. Evidence for the grounds must be provided when an extension is requested. Students are required to apply for an extension to the Course Co-ordinator before the assessment task is due. Extensions will not be provided on the grounds of poor prioritising of time. The assessment extension application form can be obtained from:

    Penalty for Late Submission of Assessment Tasks
    Assessment tasks must be submitted by the stated deadlines. There will be a penalty for late submission of assessment tasks: the submitted work will be marked ‘without prejudice’ and 10% of the obtained mark will be deducted for each working day (or part of a day) that an assessment task is late, up to a maximum penalty of 50% of the mark attained. An examiner may elect not to accept any assessment task that a student wants to submit after that task has been marked and feedback provided to the rest of the class.

    Late submission of assessments
    If an extension is not applied for, or not granted then a penalty for late submission will apply. A penalty of zero will be allocated to late submitted assessment.
    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 Access Adelaide.

  • 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 ( 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.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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