QBUS2810: Statistical Modelling for Business

Learning Outcomes

• Modelling principles: Understand the core principles of statistical modelling for business-related variables.
• Quantifying relationships: Measure and analyse relationships between variables using a range of quantitative models and methods to support decisions.
• Decision support: Translate empirical relationships into actionable, data-informed business recommendations.
• Data management: Manage data pipelines and extract objective quantitative information for analysis.
• Software proficiency: Build competence using Python and related tools to analyse relationships and work with large datasets.
• Communication: Report empirical findings with appropriate statistical language, clear visualisations, and plain-English explanations for stakeholders.

Takeaways

This course is helping me build a more systematic understanding of how statistical models can be used to explain business problems rather than only describe data. The most important takeaway is learning how to translate messy business questions into measurable modelling tasks. Instead of treating data analysis as simply running Python code, QBUS2810 trains me to think about what relationship I am trying to test, which variables matter, what assumptions the model depends on, and how the results can support a real decision. I am also developing stronger practical skills in using Python for data cleaning, exploratory analysis, modelling, forecasting, and visualisation. These skills are especially useful for my data projects because they help me move from raw datasets to structured evidence and clear business insights. Another key takeaway is the importance of communication. A model is only useful when its results can be explained clearly to people who may not have a statistical background. This course is training me to interpret coefficients, uncertainty, model performance, and limitations in a way that connects technical analysis with business reasoning. Overall, QBUS2810 strengthens both my quantitative foundation and my ability to use data as a decision-making tool. It connects statistics, coding, and business interpretation, which is directly relevant to my interests in data analytics, product strategy, and AI-driven decision support.