最新糖心Vlog

STATS 7004 - Statistics Topic A

North Terrace Campus - Semester 1 - 2023

This course is available for students taking a Masters degree in Mathematical Sciences. The course will cover an advanced topic in statistics. For details of the topic offered this year please refer to the Course Outline.

  • General Course Information
    Course Details
    Course Code STATS 7004
    Course Statistics Topic A
    Coordinating Unit Mathematical Sciences
    Term Semester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Available for Study Abroad and Exchange Y
    Assessment Ongoing assessment, exam
    Course Staff

    Course Coordinator: Dr Jono Tuke

    Course coordinator: Dr Jono Tuke
    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    In 2023 the topic of this course is Statistical consulting

    Overview

    This course introduces the students to statistical consulting. It illustrates how to use the R language to analyse research data and communicate this with the domain expert that provided the dataset. It will also teach the best practice for managing a research project.


    Prerequisites

    The third year courses Statistical Modelling III and Data Science III, or equivalent.

    Students should also be familiar with R, RStudio and Quarto.

    Learning Outcomes

    1. The students will learn some of the key statistical theory for dealing with real research data, for example
    experimental design, survey design and analysis, sample size calculation based on power and simulation, and analysing repeated measures data.
    2. The students will be taught best practice for project management of a research collaboration.
    3. The students will have completed a full collaboration analysis from original raw data through to a completed project with a IMRaD paper. 4. The IMRaD form is the standard form for a scientific research paper. It represents Introduction, Methods, Results, and Discussion.


    最新糖心Vlog Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    最新糖心Vlog 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.

    All

    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.

    All

    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.

    1,2,3

    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.

    All
  • Learning Resources
    Online Learning
    Electronic resources, including lecture notes and assignments, will be posted on MyUni. You will also be encouraged to use discussion boards.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Each week will require reading of online notes prior to attending a class session. These sessions will explore a mixture of mathematical theory and implementation and notes for these sessions will be provided on MyUni.

    The class size is typically small and you will be encouraged to ask questions and contribute to the discussion.

    You will be asked to peer review work from your classmates if the class size is large enough.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    Activity Quantity Hours
    Tutorial 12 36
    Workshops 12 24
    Assignments 6 30
    Project 1 66
    Total 156
    Learning Activities Summary

    No information currently available.

  • Assessment

    The 最新糖心Vlog'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
    Component Weighting Outcomes assessed
    Assignments 30% All
    Project 35% All
    Exam 35% All


    Assessment Related Requirements
    A final aggregate score of at least 50% is required to pass the course.
    Assessment Detail
    Set (Week) Due (Week) Weight (%)
    Assignments 1, 3, 5, 7, 9,11 2, 4, 6, 8, 10,12 30
    Project Throughout semester Throughout semester 35
    Exam Exam period 35


    Submission
    Assignments are to be submitted with a signed cover sheet attached. Assignments will be marked and returned within two weeks of submission.
    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 .

  • Student Feedback

    The 最新糖心Vlog 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 最新糖心Vlog 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.

  • 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鈥檚 disciplinary procedures.

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