COMMERCE 7015RES - Business Statistics (M)

North Terrace Campus - Semester 1 - 2015

This course aims to provide students with a sound understanding of theoretical statistical principles as well as advanced practical skills in the application of statistics. The course assumes no prior knowledge of statistics and beginning with elementary concepts develops to consider advanced concepts such as multivariate regression and time series analysis. Modelling and analysis is frequently placed within a business context, with roughly equal emphasis on theory and its application.

  • General Course Information
    Course Details
    Course Code COMMERCE 7015RES
    Course Business Statistics (M)
    Coordinating Unit Business School
    Term Semester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 36 hours
    Available for Study Abroad and Exchange N
    Restrictions Restricted to Honours, Masters of Philosopy, Masters of Business Research and PhD students only.
    Course Description This course aims to provide students with a sound understanding of theoretical statistical principles as well as advanced practical skills in the application of statistics. The course assumes no prior knowledge of statistics and beginning with elementary concepts develops to consider advanced concepts such as multivariate regression and time series analysis. Modelling and analysis is frequently placed within a business context, with roughly equal emphasis on theory and its application.
    Course Staff

    Course Coordinator: Mr Dale Blackmore

    Lecturer in Charge Name: Dale Blackmore
    Location: Room 13.51, Level 13, 10 Pulteney Street Adelaide South Australia 5000
    Telephone: +61 8 8313 0083
    Email: dale.blackmore@adelaide.edu.au
    Course Timetable

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

    Week
    Topic
    1 Data Collection, Identification and Presentation
    2 Describing Data and Test Determination
    3 Probability Theory and Application
    4 Probability Distributions: Discrete and Continous
    5 Data Collection through surveys and Sampling Distribution
    6 The Concept of Interval Estimation and Hypothesis Testing and Analysis
    7 Analysis of Variance
    8 Simple Regression Analysis
    9 Multivariate Regression Analysis
    10 Multivariate Regression Analysis
    11 Chi-Square and other Non-Parametric Analysis
    12 Test Identification
  • Learning Outcomes
    Course Learning Outcomes
    • Explain probability theory and probability distributions in relation to general statistical analysis
    • Analyse and contrast techniques and biases of quantitative methods within the context they are to be applied
    • Evaluate sampling methodologies and their associated analysis.
    • Design, evaluate and apply regression analysis
    • Critically evaluate statistical results
    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, 4, 5
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 1, 2, 3, 4, 5
    A proficiency in the appropriate use of contemporary technologies. 4
  • Learning Resources
    Required Resources
    Doane, D.P.& Seward, L. E. (2010). Applied Statistics in Business and Economics (3rd ed.). Sydney: McGraw - Hill Irvin.
    ISBN:0073373699
    ISBN -13:9780073373690
    Online Learning
    MyUni will be utilised to provide additional interaction between students and staff, especially in the evaluation and discussion of the various techniques identified during class.
    Please check your student email and MyUni as course - related announcements are communicated via email and also posted onto MyUni.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Primary content delivery occurs through weekly discussions in class. These discussions are closely linked to and supported by the course text - Applied Statistics in Business and Economics (3rd ed.). Secondary learning modes include an online discussion forum motivated
    by questions from the teaching staff and optional consultations with the lecturer in charge.
    Workload

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

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
    While individual time commitments may vary, most students will generally find themselves within the following recommended guidelines:
    Weekly class: 2hours per week
    Discussion forum: 1 hour per week
    Major project: average of 1- 2 hours per week
    Self - study: 6 - 8 hours per week
    Learning Activities Summary

    No information currently available.

  • 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 Weighting Related learning outcome
    Class test 10% 1-2
    Group assignment 50% 1-5

    Final exam

    Take home paper

    40% 1-5
    Assessment Detail

    Problem Set
    A selection of textbook and other exercises designed to allow students to apply the theory and methods discussed in class.

    Major Project – Case Study with Data Analysis
    An “hypothetical” scenario requiring comprehensive implementation of the full range of statistical methods discussed during the course.

    Final Examination
    A timed exercise covering all topics considered in the course.

    Submission
    1. All assessment pieces must be submitted on or before the stated due date
    2. Late submissions will be accepted but will incur a penalty of a 10% grade deduction for each calendar day (or part of a day) late.
    3. Applications for extension of assessment hand-in may be granted in some circumstances. All such applications must be made in writing to the lecturer in charge.
    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 (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’s disciplinary procedures.

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