ETB1100 · Business statistics

Overview

You will learn to collect, analyse and interpret business data to support evidence-based decisions in areas such as accounting, finance, management and marketing, and to clearly communicate your findings. Statistical techniques are introduced as tools for real problems: summarising and visualising data to reveal patterns, using probability to reason about risk, applying inference to judge whether observed effects are credible, modelling relationships between variables with regression to inform recommendations, and using time series methods to make short-term forecasts. You will also critically use AI-enabled digital tools in regression analyses of equity-related issues, evaluating their outputs and limitations while reflecting on implications for diversity and inclusion in business decision-making. Excel software will be used.

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. apply descriptive statistical and spreadsheet techniques to summarise and visualise business data sets to support initial business insights
2. apply basic probability concepts and common probability distributions to quantify and interpret risk and uncertainty in business decision scenarios
3. estimate and draw statistical inference about population parameters (e.g. means and proportions) in order to validate the evidence used in business decisions
4. analyse relationships between business variables using correlation and simple linear regression to generate and justify data-driven recommendations for decision-makers
5. apply basic time series techniques to describe patterns in business data and produce short-term forecasts that inform business planning and performance evaluation
6. evaluate contemporary digital tools, including AI-enabled technologies, as used to support 'in-context' interpretations of the regression findings around issues related to equity, diversity and inclusion.

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

Student experience, not official rules. Nothing here changes what the Handbook says.