| | Learning outcome |
|---|
| 1 | Exhibit a broad and coherent body of knowledge in fundamental principles of probability theory and statistics, including the principles of decision-making under uncertainty and statistical hypothesis testing |
|---|
| 2 | Exhibit a deep and comprehensive knowledge of statistical reasoning and inference methods, the framework of statistical hypothesis testing and common statistical procedures |
|---|
| 3 | Formulate statistical questions in a disciplinary context and identify and apply appropriate techniques and statistical reasoning to prepare and analyse data |
|---|
| 4 | Analyse data in descriptive, interpretive and exploratory ways using graphical methods and visualisation tools |
|---|
| 5 | Identify and address gaps in their statistical knowledge and skills by independently sourcing, collating and synthesising appropriate resources that extend their understanding of statistical concepts |
|---|
| 6 | Communicate statistical concepts, methodology and results to diverse audiences using a variety of models including to facilitate data-driven decision-making |
|---|
| 7 | Use computer resources and statistical programming languages to address a broad range of statistical questions |
|---|
| 8 | Construct robust experimental designs using statistical principles |
|---|
| 9 | Address practical and abstract statistical problems using a range of concepts, techniques and technologies, working professionally, ethically and responsibly and with consideration of cross-cultural perspectives, within collaborative, interdisciplinary teams |
|---|
