Course outline Code: BUS501 Title: Business Analytics and Statistics Faculty of Arts, Business and Law School of Business Teaching Session: Semester 2 Year: 2017 Course Coordinator: Dr Jenna Campton Office: SouthBank Telephone: (07) 5409 8627 Email: jcampton@usc.edu.au 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) Generalising 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
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: You will be assessed on the learning outcome in task/s: Completing these tasks successfully will contribute to you becoming: 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. 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 4.5 Specific assumed prior knowledge and skills N/A
Page 3 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 7, inclusive Individual 40% 1500 words Week 11, Monday Individual 50% 2 hours Central examination Period 100% Where should I submit it? Online On Blackboard In exam venue Assessment Task 1: In class quizzes Goal: To assess your assimilation of material presented within the lectures. Product: Online quizzes. Format: From Week 3 to Week 7 (inclusive) an online quiz will be conducted each week. Each quiz will comprise 5 multiple choice questions. This is an individual assessment. Criteria Each quiz is worth 2 marks 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: To undertake a business analytics approach to solve a set of business problems that require the use of appropriately selected business analytics approaches. Product: Research Project. Format: This is an individual assessment. Students will be given a dataset and problem definition. The assessment will report the business problem, and business analytics tools selected to solve the selected problem(s). This is followed by a technical analysis and discussion of practical results. The format of the report will comprise of: Introduction Problem definition and business intelligence required Selected analytics methods and technical analysis Results Discussion Criteria To be presented on Blackboard. Generic skill assessed Skill assessment level Problem solving Information literacy Applying technologies
Assessment Task 3: Final examination Page 4 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 Plagiarism In order to minimise incidents of plagiarism and collusion, this course may require that some of its assessment tasks, when submitted to Blackboard, are electronically checked through SafeAssign. This software allows for text comparisons to be made between your submitted assessment item and all other work that SafeAssign has access to. 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 Lab: 1 hour per week (Weeks 2-13) 6.2 Teaching semester/session(s) offered Semester 2
Page 5 6.3 Course activities Teaching Week / What key concepts/content will I learn? What activities will I engage in to learn the concepts/content? Module Directed Study Activities Independent Study Activities 1 Introduction to business intelligence and business analytics; data measurement scales No Lab 2 Introduction to IBM SPSS; Graphical displays, Data visualisation, introduction to dashboards Lab: Week 2 Week 2 readings 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 Generalising from data analysis to wider business conclusions and decisions (hypothesis testing, and confidence intervals) 7 Generalising from data analysis to wider business conclusions and decisions (hypothesis testing, and confidence intervals) Lab: Week 3 Lab: Week 4 Lab: Week 5 Lab: Week 6 Lab: Week 7 8 Comparing means Lab: Week 8 9 Chi-square and contingency table Analysis 10 Monday, 2 nd October Queen's Birthday Public Holiday Mid Semester Break Correlation, simple linear regression, and outliers Lab: Week 9 Lab: Week 10 11 Predictive analytics: Multiple linear regression Lab: Week 11 12 Predictive analytics: Multiple linear regression: multicollinearity and autocorrelation Lab: Week 12 13 Review and revision Lab: Week 13 Study Period Central Examination Period End of Semester Break Please note that the course activities may be subject to variation. 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 Week 12 readings Week 13 readings
Page 6 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: http://www.wileydirect.com.au/buy/australasianbusiness-statistics-core-concepts-3rd-edition/ 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 Health and safety risks have been assessed as low. It is your responsibility to research and understand risks of specific courses and to review the USC s health and safety principles by viewing the online induction training for students. 8. How can I obtain help with my studies? In the first instance you should contact your tutor, then the Course Coordinator. Additional assistance is provided to all students through Peer Advisors and Academic Skills Advisors. You can drop in or book an appointment. To book: Tel: +61 7 5430 2890 or Email: studentcentral@usc.edu.au 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 http://www.usc.edu.au/university/governance-and-executive/policies-and-procedures#academic-learningand-teaching 10. General enquiries In person: Sippy Downs - Student Central, Ground Floor, Building C USC SouthBank - Student Central, Building B, Ground floor (level 1) USC Gympie - Student Central, 71 Cartwright Road, Gympie USC Fraser Coast - Student Central, Building A Tel: +61 7 5430 2890 Email: studentcentral@usc.edu.au