GSBS6002
Foundation of Business Analysis
10 Units
Available in 2014
| Newcastle City Precinct | Trimester 1, Trimester 2, Trimester 3 |
|---|---|
| Sydney Bathurst Street | Trimester 1, Trimester 2, Trimester 3 |
| UoN Singapore | Trimester 2 |
| WebLearn GradSchool | Trimester 1, Trimester 2, Trimester 3 |
Previously offered in 2013, 2012
Intelligent business decisions are reliant upon timely and accurate data analysis. This course introduces the data analysis techniques necessary for transforming real world business data and relationships into actionable information to assist in business decision-making. A range of data analysis techniques are covered with applications to functional areas of business – general and human resource management, marketing, international business and finance. Students will have the opportunity to learn how to use software tools to analyze data and then interpret and evaluate the results in a business context.
| Objectives | On successful completion of this course students will be able to: 1. Demonstrate an integrative understanding of the role, sources and types of business data; 2. Collect and present business data; 3. Comprehend and apply principles of hypothesis testing; 4. Apply a range of techniques for data analyses and identify their role in supporting managerial decision making; 5. Employ statistical software to analyze data; 6. Report findings from data analysis in a clear and concise manner. |
||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Content | This course consists of three modules, of which students are required to complete Module 1 and either Module 2 or Module 3. Module 1 Fundamentals of Quantitative Analysis This module is compulsory for all students enrolled in this course. It introduces students to the role of basic data analysis techniques in supporting managerial decisions, identifying and examining their strengths and weaknesses, the context in which each is applicable and how to justify business decisions based on analysis of quantitative data. Students gain a fundamental understanding of quantitative business analysis and learn the following topics over six weeks: 1. The Role of Data Analysis in the Business Decision Making Process. 2. Collecting and Presenting Quantitative Data 3. Examining Data Characteristics - Descriptive Statistics & Data Screening 4. Estimation and Hypothesis Testing 5. Correlation and Simple Regression Analysis 6. Multiple Regression Analysis Module 2 Fundamentals of Qualitative Analysis On successful completion of this module, students will be able to discuss the role of qualitative methods in supporting managerial decisions, identify and explain the strengths and weaknesses of different qualitative methods, explain the context in which each qualitative method is most applicable, justify managerial decisions based on analysis of quantitative data. Students learn the following topics over six weeks: 1. The Role and Nature of Qualitative Data Analysis 2. Collecting and Presenting Qualitative Data 3. Content Analysis 4. Case Study Method 5. Focus Group Method 6. Mixed Methods Module 3 Selected Topics in Quantitative Analysis This module begins with a discussion of common pitfalls of classical regression analysis and their implications for managerial decisions making. Students are then introduced to a range of techniques to circumvent those pitfalls as well as exposed to analytical tools suitable for evaluating moderating and mediating relationships, forecasting economic and business time series, measuring risk exposures of an economic unit and explaining discrete choices. On successful completion of this module, students will be able to apply quantitative techniques beyond classical regression analysis and appreciate their value in improving managerial decisions making. Students learn the following topics over six weeks: 1. Pitfalls of Classical Regression Analysis and their Implications for Managerial Decisions Making – Part I 2. Pitfalls of Classical Regression Analysis and their Implications for Managerial Decisions Making – Part II 3. Moderated, Mediated and Dummy Variable Regressions 4. Panel Data Analysis 5. Explaining Discrete Choices 6. Time Series Analysis of Business Forecasting |
||||||||||
| Replacing Course(s) | N/A | ||||||||||
| Transition | N/A | ||||||||||
| Industrial Experience | 0 | ||||||||||
| Assumed Knowledge | There is no assumed knowledge for this course. | ||||||||||
| Modes of Delivery | Distance Learning : IT Based Flexible Delivery / Student Centred Learning Internal Mode |
||||||||||
| Teaching Methods | Lecture
Workshop |
||||||||||
| Assessment Items |
|
||||||||||
| Contact Hours | Lecture: for 2 hour(s) per Week for 12 weeks Computer Lab: for 1 hour(s) per Week for 12 weeks |
||||||||||
| Timetables | 2014 Course Timetables for GSBS6002 |