Data Analysis

This subject has the following teaching availabilities in 2014:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

Contemporary business is awash in data. Modern business processes and activities usually involve multiple streams of data from areas as diverse as marketing activities, operational processes and financial activities. Therefore, managers are frequently confronted with how to harness these to understand their business better, so that they can make more informed decisions. This subject provides the fundamental quantitative skills necessary for an MBA student to extract information from data, through quantitative analysis, to make better managerial decisions. Students will be familiarized with the tools of quantitative analysis, develop the necessary skills for analytical thinking and a quantitative mind set in measuring performance. The fundamental quantitative skills from this subject provide a foundation to the advanced subjects within the MBA and provide students an analytical framework towards solving managerial problems later in their career.

On completion of this subject, students should be able to:

• Apply quantitative methods in management decision making processes
• Apply the principles of statistical variation when considering statistics from data
• Apply regression modeling techniques to gain a better understanding of the complex relationships between business variables
• Possess an analytical mindset in solving business problems
• Possess solid computational skills in Excel

Ole Maneesoonthorn:

• 8 x Class preparation exercises (15%)
• Equivalent of individual 300 word assessment in total
• Throughout subject
• Mid-term test (20%)
• 90 minutes
• Week 5
• Syndicate assignment(25%)
• Equivalent of individual 500 word assessment
• Week 10

• Final Examination (40%)
• Hurdle requirement
• 3 hours
• End of subject

Chris Lloyd:

• 15 x Class preparation exercises (15%)
• Throughout subject
• Mid-term test (20%)
• 90 minutes
• Week 5
• Syndicate assignment(25%)
• Week 10

• Final Examination (40%)
• Hurdle requirement
• 2 hours
• End of subject

This subject is not available as a breadth subject.