EDUC 1011 - Reasoning with Numbers: Statistical Literacy

North Terrace Campus - Semester 2 - 2021

This course covers broad quantitative skills in the context of academic reasoning and argumentation: it aims to make students literate in the use of numbers and the basic analysis of data for academic purposes. Students will be introduced to some basic statistical concepts such as summarising data, statistical distributions, basic hypothesis testing, and probability. Assessment will consist of an online quiz, a summary of a statistical paper, and a research activity where students analyses data and then present their analysis. This course will be useful for students entering courses where mathematical and statistical skills are necessary, such as Psychology, Health Sciences, or Business and Commerce disciplines. This course is compulsory for University Preparatory Program students wishing to undertaken studies in Nursing or Health Sciences.

  • General Course Information
    Course Details
    Course Code EDUC 1011
    Course Reasoning with Numbers: Statistical Literacy
    Coordinating Unit School of Education
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 3 hours per week
    Available for Study Abroad and Exchange N
    Restrictions Available to University Preparatory Program or Wirltu Yarlu Preparatory Program students only
    Assessment Mini-quizzes on statistics x 2; Statistics group presentation; Essay on application of statistics to real-life contexts
    Course Staff

    Course Coordinator: Ms Amy Robinson

    Lecturer and Tutor: Sarah James 

    Office: Level 6, Nexus10
    Phone: 08 8313 0168

    Course Timetable

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

  • Learning Outcomes
    Course Learning Outcomes
    Upon the successful completion of this course, students should be able to:

    1. Discuss and apply basic concepts which are essential in statistics, including variance, probability, significance, and others;
    2. Apply statistical knowledge to academic and everyday life;
    3. Work cooperatively with others;
    4. Analyse a specific dataset in response to a question in order to form well-supported conclusions;
    5. Utilise technology to assist in the analysis and application of statistical knowledge.
    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)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1, 2, 4, 5
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    1, 2, 3, 4, 5
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    1, 3, 4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    2, 3, 4, 5
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    3, 4
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
    2, 3
  • Learning Resources
    Required Resources
    Please see MyUni for details. 
    Recommended Resources
    Moore. D.S, McCabe. G and Craig.B.A 2014 Introduction to the Practice of Statistics, 8th Edition, W.H.Freeman and Company. 

    Online Learning
    See MyUni for details.
  • Learning & Teaching Activities
    Learning & Teaching Modes

    No information currently available.


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

    1 hour lecture per week - 12 hours

    Preparation for lectures - 12 hours

    2 hour tutorial per week - 24 hours

    Preparation for tutorials - 12 hours

    Assignments - 65 hours

    Learning Activities Summary

    Week 1: Introduction to the course and statistics 

    Week 2: Data, variables and analysis

    Week 3: Data, variables and analysis

    Week 4: Data, variables and analysis

    Week 5: Normality

    Week 6: TBC

    Week 7: Hypothesis Testing

    Week 8: Hypothesis Testing

    MID SEMESTER BREAK - Two weeks

    Week 9: Presentations

    Week 10: Linear Regression

    Week 11: Probability

    Week 12: Probability

    Weekly topics subject to change depending on cohort knowledge and skill set. 

  • 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
    Summary Formative Friday Week 5 25% 1,2,4
    Presentation Summative Friday Week 9 25% 1,2,3,4,5
    Report Summative Friday Week 13 40% 1,2,3,4,5
    Active Participation Formative Ongoing - every two weeks 10% 1,2,4,5

    For clarification on which dates correspond to which weeks, please visit:  

    Assessment Detail

    No information currently available.


    No information currently available.

    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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