QBM100 Data Analytics for Business (8)

This subject introduces the students to the role of data and data analysis in decision making in organisations, including methods of sourcing, collecting and examining relevant data.  Commonly used tools and techniques for data analysis, interpretation and presentation are then introduced, through the practical consideration of authentic data sets using relevant software.  The emphasis is on effective communication of the findings.  The subjects objective is on the development of a professional with the capacity to access, organise and analyse data in order to effectively make and convey decisions within the contemporary business context.

No offerings have been identified for this subject in 2020.

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Computing and Mathematics

Enrolment Restrictions

Students who have completed QBM117 may not enrol in QBM100.

Subject Relationships

STA201 Subject contains approximately 50% overlap of content. Subjects are sufficiently different in content and context to both be studied.
QBM120 Subject contains approximately 50% overlap of content. Subjects are sufficiently different in content and focus to both be studied.
STA401 Subject contains approximately 50% overlap of content. Subjects are sufficiently different in content and context to both be studied.
QBM117 Subject contains approximately 75% overlap of content. Subjects are similar in content and context and so are incompatible.
STA501 Subject contains approximately 50% overlap of content. Subjects are sufficiently different in content and context to both be studied.

Incompatible Subjects

QBM117

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to discuss the basic concepts relating to data analytics (including big data);
  • be able to recognise the various types and sources of data;
  • be able to extract value from data sets for informed decision making;
  • be able to identify and determine the appropriate statistical technique to analyse data:
  • be able to apply relevant software tools to summarise and analyse data; and
  • be able to present and communicate relevant decisions arising from the analysis of data.

Syllabus

This subject will cover the following topics:
  • Introduction to data (including big data), data analytics, data sources and data types
  • Methods of summarising, analysing, interpreting and presenting data numerically and graphically, using relevant software
  • Probability and probability distributions
  • Sampling and sampling techniques
  • Statistical inference of quantitative and qualitative data for a single variable
  • Simple linear regression and correlation

The information contained in the CSU Handbook was accurate at the date of publication: October 2020. The University reserves the right to vary the information at any time without notice.

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