This subject introduces students to fundamental quantitative theory and tools to support business intelligence and data analysis needs of modern organisations. This Includes basic statistics, probability distributions, correlation, regression, and time series forecasting. The emphasis of this subject is to develop practical computational skills and problem-solving capabilities utilising appropriate analytical approaches to a given problem. The tools and techniques introduced in this subject, including the use of spreadsheets for data management and analysis, can be applied to exploratory big data analysis.
Business, Commerce, and Entrepreneurship
Create appropriate graphical and numerical descriptive statistics to summarize and interpret different types of data.
Apply probability rules and concepts relating to discrete and continuous random variables to answer questions within a complex business context.
Demonstrate thorough knowledge of the importance of the Central Limit Theorem (CLT) and its applications.
Conduct and interpret a variety of hypothesis tests to aid decision making in a business context.
Use simple/multiple regression models to analyse the underlying relationships between the variables through hypothesis testing and forecast the trend.
Critically evaluate and communicate the result of a statistical analysis in a professional report.
Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have
through previous study. It is the responsibility of students to ensure they meet the assumed knowledge
expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against
enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.
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