COMMERCE 7033 - Quantitative Methods (M)
North Terrace Campus - Semester 2 - 2014
General Course Information
Course Code COMMERCE 7033 Course Quantitative Methods (M) Coordinating Unit Business School Term Semester 2 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 4 hours per week Course Description The purpose of this course is to provide an introduction to both basic and advanced analytical tools for business disciplines. Beginning with simple statistical methods, the course builds to more robust analytical techniques such as multivariate linear regression. Emphasis is placed on theoretical understanding of concepts as well as the application of key methodologies used by industry. This course also aims to promote a critical perspective on the use of statistical and econometric information.
Course Coordinator: Dr George MihaylovMr George Mihaylov (lecturer in charge)
Location: Room 12.14, Nexus 10, Pulteney Street
Telephone: 8313 2056 (work)
Email: email@example.com (preferred contact)
George is the lecturer in charge of Quantitative Methods (M) at the University of Adelaide Business School. He holds degrees in Mathematical and Computer Sciences (Statistics) and Finance (Honours). George is also a PhD candidate with the school within the field of finance. His PhD research focuses on the socio-economic impacts of shared appreciation mortgages. His other work includes academic research on financial products and services as well as industry projects through the International Centre for Financial Services.
George has a broad spectrum of teaching interests. Previously he has taught portfolio theory and management, banking, risk management and statistics.
Mr John Dolinis (tutor and workshop co-ordinator)
Email: firstname.lastname@example.org (preferred contact) OR email@example.com
John is a tutor and workshop co-ordinator for Quantitative Methods (M). He holds a Bachelor degree in Applied Mathematics and Physics; a Master degree in Public Health (epidemiology and biostatistics); and a Master degree in Accounting and Finance. He is currently teaching accounting and quantitative methods subjects at other tertiary education institutions in Adelaide. He has prior health and medical research experience, particularly in the field of injury analysis, surveillance and prevention.
The full timetable of all activities for this course can be accessed from Course Planner.The schedule of topics for this course is as follows:
1. Mathematics of the Time Value of Money – introduction to time value theory, compound interest calculations and variations
2. Data Collection and Summary Statistics – graphical and tabular data presentation, summary statistics, common errors in presentation
3. Probability Theory and Concepts – introduction to marginal, joint and conditional probability theory
4. Probability Distributions – introduction to discrete and continuous probability distributions, standard normal distribution transformation
5. Sampling Distribution and Data Collection through Surveys – sampling error, sample mean distribution, central limit theorem, sampling bias
6. The Concept of Interval Estimation – point estimates, confidence intervals and theory, student’s t distribution
7. Hypothesis Testing and Analysis – hypothesis development, significance and decision making, type 1 and 2 errors, analysis of variance (ANOVA)
8. Simple Regression Analysis – correlation, ordinary least squares, coefficient interpretation, the role of residuals in model development and evaluation, modelling assumptions
9. Multivariate Regression Analysis – model interpretation and evaluation, testing for and correcting heteroscedasticity, residual autocorrelation and multicollinearity, dummy variables
10. Introduction to Time Series Analysis and Forecasting – time series decomposition, qualitative and quantitative forecasting, model development and testing
Course Learning OutcomesBy the end of this course students should be able to:
1. Communicate effectively using statistical terminology
2. Understand probability theory and its relation to general statistics
3. Explain the importance, techniques and biases of quantitative methods in context
4. Understand sampling methodologies and analysis
5. Use estimated models to obtain point and interval predictions as well as forecasts
6. Conduct and interpret various statistical hypothesis tests
7. Understand and critically evaluate regression analysis (model selection)
8. Critically interpret statistical and econometric 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. 2, 4, 5, 6, 7 & 8 The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 4, 6, 7 & 8 An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 5, 6 & 7 Skills of a high order in interpersonal understanding, teamwork and communication. 1, 3 & 8 A proficiency in the appropriate use of contemporary technologies. 5, 6 & 7 An awareness of ethical, social and cultural issues within a global context and their importance in the exercise of professional skills and responsibilities. 3
David P. Doane & Lori E. Seward, Applied Statistics in Business and Economics, 4th ed, McGraw-Hill Irvin 2013.
This course requires mathematical computation. Although much of it is relatively simple, access to an appropriate calculator is necessary. If you intend to purchase a calculator for this course, you will find it very useful to purchase a graphics calculator.
Learning & Teaching Activities
Learning & Teaching ModesThis course will offer one 2-hour lecture per week from week 1 to week 12. In addition to the lectures, a 1-hour tutorial class will be offered from week 2 until week 12 and a 1 hour workshop will be offered from week 7 to week 10.
Tutorial classes will be held weekly commencing the week beginning (Monday 4 August). Membership of tutorial classes is to be finalised by the end of the second week of semester. Students wishing to swap between tutorial classes after this time are required to present their case to the Lecturer in Charge, but should be aware that such a request may not be approved. Tutorials are an important component of your learning in this course. The communication skills developed in tutorials by regularly and actively participating in discussions are considered to be most important by the School and are highly regarded by employers and professional bodies.
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.
The University expects full-time students (i.e. those taking 12 units per semester) to devote a total of 48 hours per week to their studies. This means that you are expected to commit approximately 9 hours for a three-unit course or 13 hours for a four-unit course, of private study outside of your regular classes.
Students in this course are expected to attend all seminars.
Learning Activities Summary
No information currently available.
The University's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Due Date and Time (& Location if applicable) Weighting Related Learning Outcome Mid-term Exam Tuesday 9 September, 5:30pm in Bonython Hall 15% 1 - 6 Major Project Wednesday 29 October, 1pm 15% 1 - 8 Final Exam See Access Adelaide 70% 1 - 8 Total 100%
Assessment Related RequirementsTo gain a pass for this course, a mark of at least 50% must be obtained on the examination as well as a total of at least 50% overall. Students who achieve 50% or more overall but not the minimum exam mark of 50% will be awarded no more than 49% for the full course. Students in this position will be offered an academic supplementary examination.
Legible hand-writing and the quality of English expression are considered to be integral parts of the assessment process. Marks may be deducted in all assessments because of poor hand-writing or English expression.
Students in this course are not permitted to take a DICTIONARY (English or English-Foreign) into the examination.
The use of calculators in the examination is permitted in this course; however graphics calculators must have their memory wiped by exam invigilators.
Students are also permitted to bring into the examination, 1 double sided A4 page of hand-written notes. If this note page contains computer writing, it will be confiscated and students may be reported for academic misconduct.
No information currently available.
SubmissionThe 1 hour mid-term exam will be held in class during the weekly lecture in week 6 – test papers are to be submitted immediately following this time. Major project submissions are to be made through the postgraduate hub at Nexus 10 Pulteney Street.
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.
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.
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