FIN5003 Decision Support Tools
|Semester 1, 2013 On-campus Springfield|
|Faculty or Section :||Faculty of Business and Law|
|School or Department :||School of Accounting, Economics and Finance|
|Version produced :||21 July 2014|
Examiner: Dom Pensiero
Moderator: Glenda Adkins
Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at http://www.usq.edu.au/current-students/support/computing/hardware.
Managers receive vast quantities of data, translate it to information, disseminate this within the organisation, analyse it, and interpret the outcomes in order to make informed and balanced decisions. This course is designed to improve the quality of management decision-making by the introduction of relevant statistical, operations research and operations management techniques. These techniques aim to bridge the gap between the theory and practical application of quantitative techniques as decision support tools.
The course aims to enhance the ability of managers to make decisions by formulating real world problems, often featuring ambiguity, in a manner which allows the application of quantitative management tools. The generalised approach of problem formulation, modelling, solution, interpretation and implementation will be addressed. The course will deal with the issues of data reduction, inference testing, forecasting, decision analysis, scheduling, location and layout decisions, Just-In-Time, project management and quality management. Formerly MGT5001.
On successful completion of this course, students should be able to:
- demonstrate problem-solving skills in being able to assess, organise, summarise, present and interpret data for decision-making purposes; and be conversant with ethical issues when analysing data using the tools available
- incorporate academic and professional literacy by demonstrating a systematic approach to decision-making by applying decision theory to business situations, determining how much additional data is required through problem-solving skills such as Bayesian probability analysis, and assessing whether it is cost effective to do so
- apply problem-solving and academic and professional literacy skills on determining the relevant simple regression and correlation coefficients for a data set reflecting a given business situation and interpret the validity of the results obtained models with respect to ethical issues and validity
- select the forecasting tools applicable to a given situation, choose the most relevant, apply, and then assess the validity and limitations of the outcomes through a combination of problem-solving skills, academic and professional literacy and ethical issues
- analyse and apply appropriate confidence interval and hypothesis testing procedures for given data sets using problem-solving skills, and then assess applications to business problems in the context of ethical issues and enquiry
- understand and describe the relevant tools available in establishing and managing a quality management system in the context of academic and professional literacy (eg ISO9001:2000 and ISO14000); apply these tools to the analysis of organisational systems seeking to control quality through problem-solving skills such as construction of p, c , mean and range charts
- understand and describe the importance of project management in a wider academic and professional literacy context, apply project principles to given cases, interpret the outcomes and use problem-solving skills to construct network diagrams, calculate critical paths, ES,EF.LS and LF activity times, apply CPM/PERT methodology to network problems, undertake crashing and probability of project completion times to project management problems
- apply selected qualitative and quantitative managerial tools to linear programming, scheduling, location, layout problems and simulations in academic and professional literacy applications by using a variety of problem-solving skills and tools such as the graphical method of linear programming; assignment method, Johnsons rule and scheduling rules such as FCFS,SPT,LPT,EDD and CR.
|2.||Use of continuous distributions||15.00|
|3.||Regression and correlation||15.00|
|6.||Selected management decision tools||35.00|
Text and materials required to be purchased or accessed
ALL textbooks and materials available to be purchased can be sourced from USQ's Online Bookshop (unless otherwise stated). (https://bookshop.usq.edu.au/bookweb/subject.cgi?year=2013&sem=01&subject1=FIN5003)
Please contact us for alternative purchase options from USQ Bookshop. (https://bookshop.usq.edu.au/contact/)
FIN5003 Decision Support Tools custom publication - compiled for the University of Southern Queensland by Dom Pensiero, Pearson Australia. This custom publication comprises readings from the Heizer & Render text and the Levine et al text.
Heizer, J & Render B 2011 global edition, Operations management, 10th edn., Pearson Education, Upper Saddle River, New Jersey (custom publication - various chapters). Chapters 3, 6, 15, Supplement 6, Quantitative Module B, Solutions.
Levine, DM, Berenson, ML, Stephan, D & Kriehbiel, TC 2011 global edition, Statistics for managers using Microsoft Excel, 6th edn., Pearson Prentice Hall, Upper Saddle River, New Jersey; (custom publication - various chapters). Chapters 1 - 4, 6 - 9, 13, 16, 19, Appendices A - C and E.
Students should note that the custom publication is ONLY available through the USQ Bookshop. If you choose not to purchase the custom publication, you may subsequently find you cannot purchase the individual texts from your local supplier/bookstore or you may find that you will have to purchase the FULL version of each text rather than the substantially cheaper and smaller customised version. Further, as texts can be released in differing editions in different countries, to avoid confusion, the study material is specifically written to the editions of the texts shown above and which are used in the custom publication. In sum, the custom publication is strongly recommended for all students.
Berenson, ML, Levine, D, Krehbiel, TC, Watson, J, Jayne, N & Turner, LW 2009, Business statistics: concepts and applications, Pearson Education, Frenchs Forest, New South Wales.
Groebner, DF, Shannon, PW, Fry, PC & Smith, KD 2008, Business statistics: a decision-making approach, 7th edn, Prentice Hall, Harlow, England.
Keller, G 2009, Statistics for management and economics, 8th edn, South-Western Cengage Learning, Belmont, California.
Krajewski, LJ, Ritzman, LP & Malhotra, MK 2010, Operations management: processes and supply chains, 9th edn, Prentice Hall, Upper Saddle River, New Jersey.
Levine, DM, Krehbiel, TC & Berenson, ML 2010, Business statistics: a first course, 5th edn, Pearson/Prentice Hall, Upper Saddle River, New Jersey.
Student workload requirements
|Description||Marks out of||Wtg (%)||Due Date||Notes|
|CMA TEST 1||5||5||14 Mar 2013||(see note 1)|
|CMA TEST 2||35||35||15 May 2013||(see note 2)|
|2-HOUR EXAMINATION||60||60||End S1||(see note 3)|
- CMA test 1 will comprise multiple-choice questions on module 1. Students can access CMA test 1 from the first week of the teaching semester.
- CMA test 2 will comprise multiple-choice questions on modules 2 - 5. Students can access CMA test 2 approximately four (4) weeks prior to the due date, that is, from 15 April 2013.
- The examination is scheduled to be held in the end-of-semester examination period. Students will be advised of the official examination date after the timetable has been finalised.
Important assessment information
It is the students' responsibility to attend and participate appropriately in all activities (such as lectures, tutorials, laboratories and practical work) scheduled for them, and to study all material provided to them or required to be accessed by them to maximise their chance of meeting the objectives of the course and to be informed of course-related activities and administration.
Requirements for students to complete each assessment item satisfactorily:
To satisfactorily complete an individual assessment item a student must achieve at least 50% of the marks. (Depending upon the requirements in Statement 4 below, students may not have to satisfactorily complete each assessment item to receive a passing grade in this course.)
Penalties for late submission of required work:
If students submit assignments after the due date without prior approval of the examiner, then a penalty of 5% of the total marks gained by the student for the assignment may apply for each working day late up to ten working days at which time a mark of zero may be recorded.
Requirements for student to be awarded a passing grade in the course:
To be assured of receiving a passing grade a student must achieve at least 50% of the total weighted marks available for the course.
Method used to combine assessment results to attain final grade:
The final grades for students will be assigned on the basis of the aggregate of the weighted marks obtained for each of the summative assessment items in the course.
This will be an open examination. Candidates may have access to any printed or written material and a calculator during the examination.
Examination period when Deferred/Supplementary examinations will be held:
Any Deferred or Supplementary examinations for this course will be held during the next examination period.
University Student Policies:
Students should read the USQ policies: Definitions, Assessment and Student Academic Misconduct to avoid actions which might contravene University policies and practices. These policies can be found at http://policy.usq.edu.au.
Assignments: (i) The due date for an assignment is the date by which a student must submit the assignment to the USQ. (ii) Students must retain a copy of each item submitted for assessment. This must be produced within 24 hours if required by the examiner. As a general rule an extension of time will be granted if appropriate documentary evidence is attached with the assessment when submitted, for example, medical certificate, letter from employer etc. Note that no extensions can be granted once model answers have become publicly available. This is generally 2 - 3 weeks after the due date. (iii) In the event that a due date for an assignment falls on a local public holiday in their area, such as a show holiday, the due date for the assignment will be the next day. Students are to note on the assignment cover the date of the public holiday for the examiner's convenience.
Course weightings: Course weightings of topics should not be interpreted as applying to the number of marks allocated to questions testing those topics in an examination paper.
Referencing in assignments: Harvard (AGPS) is the referencing system required in this course. Students should use Harvard (AGPS) style in their assignments to format details of the information sources they have cited in their work. The Harvard (AGPS) style to be used is defined by the USQ Library's referencing guide at http://www.usq.edu.au/library/referencing.
Supplementary work: Supplementary examinations may be awarded to students who have achieved at least 45% - 49% in aggregate but who are otherwise not eligible for the grade of LP (Low Pass), and who have demonstrated sufficient understanding in the examination to warrant consideration for a supplementary examination (normally a minimum of 45% achievement in the examination is required).
Deferred work: Students who, for medical, family/personal, or employment-related reasons, are unable to complete an assignment or to sit for an examination at the scheduled time may apply to defer an assessment in a course. Such a request must be accompanied by appropriate supporting documentation. One of the following temporary grades may be awarded: IDS (Incomplete - Deferred Examination); IDM (Incomplete Deferred Make-up); IDB (Incomplete - Both Deferred Examination and Deferred Make-up).
Makeup work: (i) Students who have undertaken all of the required assessments in a course but who have failed to meet some of the specified objectives of a course within the normally prescribed time may be awarded the temporary grade: IM (Incomplete - Makeup). An IM grade will only be awarded when, in the opinion of the examiner, a student will be able to achieve the remaining objectives of the course after a period of non-directed personal study, for example, a makeup assignment may be awarded to students who have passed the final examination (that is, achieved at least 50% in the final examination) but who have not achieved a composite score of 50% or more in the course.
Computer, e-mail and Internet access: Students are required to have access to a personal computer, e-mail capabilities and Internet access to UConnect. Current details of computer requirements can be found at http://www.usq.edu.au/current-students/support/computing/hardware.