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Course Outlines

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.

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  • General Course Information
    Course Details
    Course Code COMMERCE 7015RES
    Course Business Statistics (M)
    Coordinating Unit ÐÂÀ˲ÊƱ 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 Staff

    Course Coordinator: Mr Dale Blackmore

    Lecturer in Charge Name: Dale Blackmore
    Location: Room 13.51, Level 13, 10 Pulteney Street ÐÂÀ˲ÊƱ 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 .

    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 pe