Course outline. Code: BUS501 Title: Business Analytics and Statistics

Transcription

1 Course outline Code: BUS501 Title: Business Analytics and Statistics Faculty of Arts and Business School of Business Teaching Session: Semester 2 Year: 2015 Course Coordinator: Professor Willem Selen Office: K2.01 Telephone: (07) [email protected] Consultation Times: As advised on Blackboard 1. What is this course about? 1.1 Course description This course explores the use of, and techniques used in, descriptive and predictive analytics. It covers elements of data discovery and collection, data quality, analysis and data sharing, and generalising data analytics results to wider business conclusions and decisions. It makes reference to IBM Cognos as an example of a business analytics tool, combined with IBM SPSS software, applied to a wide variety of business applications, including estimation and predictive analysis. 1.2 Course content Introduction to business intelligence and business analytics Introduction to IBM SPSS and reference to IBM Cognos Data quality, graphical displays, and concepts of measurement Data measures of central tendency, variation, distributions, and outliers Sampling and data collection methods, including survey analysis (recoding and composite measures in SPSS) Generalizing from data analysis to wider business conclusions and decisions (hypothesis testing, and confidence intervals) Comparing means Chi-square and contingency table analysis Linear regression (single and multiple) Correlation and coefficient of determination Estimation and predictive analysis Dashboards and translating technical analysis into everyday language Data collection, sharing, analysis, and dissemination 2. Unit value 12 units

2 Page 2 3. How does this course contribute to my learning? Specific Learning Outcomes Assessment Tasks Graduate Qualities On successful completion of this course you should be able to: Understand the principles of business analytics and its relation to business intelligence; and applied statistical terminology and techniques. Identify a business problem, nominate an appropriate business analytics approach to address the problem and apply that business analytics approach. Apply appropriate quantitative techniques for descriptive and predictive business analytics. Make reasoned decisions as to the appropriate data collection method(s) for specific business analytics applications. Apply computer technology in the solution of business analytics problems. You will be assessed on the learning outcome in task/s: Completing these tasks successfully will contribute to you becoming: 1, 2 and 3 Creative and critical thinkers. Ethical. 1, 2 and 3 Knowledgeable. 2 and 3 Creative and critical thinkers. 1 and 2 Creative and critical thinkers. 2 and 3 Empowered. 4. Am I eligible to enrol in this course? Refer to the Coursework Programs and Awards - Academic Policy for definitions of pre-requisites, corequisites and anti-requisites 4.1 Enrolment restrictions Must be enrolled in a postgraduate program 4.2 Pre-requisites Nil 4.3 Co-requisites Nil 4.4 Anti-requisites Nil

3 Page Specific assumed prior knowledge and skills N/A 5. How am I going to be assessed? 5.1 Grading scale Standard High Distinction (HD), Distinction (DN), Credit (CR), Pass (PS), Fail (FL) 5.2 Assessment tasks Task No. Assessment Tasks Individual or Group 1 In class quizzes 2 Research project 3 Final examination Weighting % What is the duration / length? When should I submit? Individual 10% 500 words Weeks 3 to 12, inclusive Individual 40% 2000 words Week 11, Monday Individual 50% 2 hours Central examination Period 100% Where should I submit it? In class In computer lab In exam venue Assessment Task 1: In class quizzes Goal: To assess your assimilation of material presented within the lectures. Product: In class quizzes. Format: From Week 3 to Week 12 (inclusive) an in-class quiz will be conducted each week. Each quiz will comprise 5 questions which may be multiple choice or short answer. This is an individual assessment. Criteria Each quiz is worth 1 mark for a total of 10 marks across all quizzes. Individual items will be equally weighted and marked as correct or incorrect. Generic skill assessed Skill assessment level Problem solving Assessment Task 2: Research project Goal: Product: Format: To undertake a business analytics approach to solve a set of business problems that require the use of appropriately selected business analytics approaches.. Research Project. This is an individual assessment. The assessment will report the set of business problems, data required, and business analytics tools selected to solve the selected problems. The format of the report will comprise of: introduction problem definition and business intelligence required data collection selected analytics methods and technical analysis results

4 Page 4 discussion Criteria To be presented on Blackboard. Generic skill assessed Skill assessment level Problem solving Information literacy Applying technologies Assessment Task 3: Final examination Goal: This assessment task may examine all material covered in this course. Product: Final examination Format: A final examination will be held in the examination period. This two-hour examination will consist of a set of 50 multiple choice questions. This is an individual assessment. Criteria The marks for each question will be included in your exam paper. The final exam is worth 50 marks. Generic skill assessed Skill assessment level Problem solving Information literacy 5.3 Additional assessment requirements SafeAssign In order to minimise incidents of plagiarism and collusion, this course may require that some of its assessment tasks are submitted electronically via SafeAssign. This software allows for text comparisons to be made between your submitted assessment item and all other work that SafeAssign has access to. If required, details of how to submit via SafeAssign will be provided on the Blackboard site of the course. Eligibility for Supplementary Assessment Your eligibility for supplementary assessment in a course is dependent of the following conditions applying: a) The final mark is in the percentage range 47% to 49.4% b) The course is graded using the Standard Grading scale c) You have not failed an assessment task in the course due to academic misconduct 5.4 Submission penalties Late submission of assessment tasks will be penalised at the following maximum rate: 5% (of the assessment task s identified value) per day for the first two days from the date identified as the due date for the assessment task. 10% (of the assessment task s identified value) for the third day 20% (of the assessment task s identified value) for the fourth day and subsequent days up to and including seven days from the date identified as the due date for the assessment task. A result of zero is awarded for an assessment task submitted after seven days from the date identified as the due date for the assessment task. Weekdays and weekends are included in the calculation of days late. To request an extension you must contact your course coordinator to negotiate an outcome. 6. How is the course offered? 6.1 Directed study hours On campus Lecture: 2 hours per week (Weeks 1-13) On campus 1 hour per week (Weeks 2-13)

5 Page Teaching semester/session(s) offered Semester Course activities Teaching What key concepts/content will I Week / learn? Module What activities will I engage in to learn the concepts/content? Directed Study Independent Study Activities Activities 1 Introduction to business intelligence and business analytics; data measurement scales 2 Introduction to IBM SPSS; Graphical displays, Data visualization, introduction to dashboards 3 Measures of central tendency, variation, distributions, and outliers, box-and-whisker plot 4 Discrete and continuous distributions Normality plot, Assessing data quality 5 Sampling and data collection methods, including survey analysis (recoding and composite measures in SPSS) 6 Generalizing from data analysis to wider business conclusions and decisions (hypothesis testing, and confidence intervals) 7 Generalizing from data analysis to wider business conclusions and decisions (hypothesis testing, and confidence intervals) No SPSS Computer Lab Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 8 Comparing means Week 8 9 Chi-square and contingency table analysis 10 Monday, 5 th October Labour Day Public Holiday Mid Semester Break Correlation, simple linear regression, and outliers 11 Predictive analytics: Multiple linear regression Week 9 Week 10 Week 11 Week 2 readings Week 3 readings Week 4 readings Week 5 readings Week 6 readings Week 7 readings Week 8 readings Week 9 readings Week 10 readings Week 11 readings

6 12 Predictive analytics: Multiple linear regression: multicollinearity and autocorrelation Page 6 Week 12 readings Week Review and revision Week 13 Study Period Central Examination Period End of Semester Break Please note that the course activities may be subject to variation. Week 13 readings 7. What resources do I need to undertake this course? 7.1 Prescribed text(s) Please note that you need to have regular access to the resource(s) listed below: Author Year Title Publisher Black, K. et.al 2013 Australasian business statistics(3 rd Edition) E text: John Wiley & Sons Australia Ltd. 7.2 Required and recommended readings Lists of required and recommended readings may be found for this course on its Blackboard site. These materials/readings will assist you in preparing for tutorials and assignments, and will provide further information regarding particular aspects of your course. 7.3 Specific requirements N/A 7.4 Risk management There is minimal health and safety risk in this course. It is your responsibility to familiarise yourself with the Health and Safety policies and procedures applicable within campus areas. 8. How can I obtain help with my studies? In the first instance you should contact your tutor, then the Course Coordinator. Student Life and Learning provides additional assistance to all students through Peer Advisors and Academic Skills Advisors. You can drop in or book an appointment. To book: Tel: or [email protected] 9. Links to relevant University policies and procedures For more information on Academic Learning & Teaching categories including: Assessment: Courses and Coursework Programs Review of Assessment and Final Grades Supplementary Assessment Administration of Central Examinations Deferred Examinations Student Academic Misconduct Students with a Disability

7 Page Faculty specific information Locating Journal Articles If you have been notified that the journal articles in this course are available on e-reserve, use the on-line library catalogue to find them. For journal articles not on e-reserve, click on the "Journals and Newspapers" link on the Library Homepage. Enter the journal title e.g. History Australia, then search for the volume and issue or keyword as needed. Assignment Cover Sheets The Faculty of Arts and Business assignment cover sheet can be found on Blackboard or on the USC Portal at: Faculty of Arts and Business (Students) > Forms. It must be completed in full identifying student name, assignment topic, tutor and tutorial time. This must be attached securely to the front of each assessment item prior to submission. Claims of loss of assignments will not be considered unless supported by a receipt. Help: If you are experiencing problems with your studies or academic work, consult your tutor in the first instance or the Course Coordinator as quickly as possible. Difficulties: If you are experiencing difficulties relating to teaching and assessment you should approach your tutor in the first instance. If not satisfied after that you should approach in order your Course Coordinator, Program Coordinator then Head of School. General enquiries and student support Faculty Student Centre Tel: Fax: [email protected]