| 1 | <p>Describe the components of the generalized linear model and identify suitable applications for different types of glm's.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Solution-Seeking</strong></p> </p> |
| 2 | <p>Understand and explain how regression modelling is affected by measurement error, missing data, sampling, and censoring</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p><p><strong style="color: rgb(73, 80, 87);">Solution-Seeking</strong></p> </p> |
| 3 | <p>Use cross-validation to select a suitable predictive model for a given data set and evaluate the precision of the model.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p> </p> |
| 4 | <p>Create a causal graph for a given scenario and use the graph to identify confounding among the explanatory variables.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p> </p> |
| 5 | <p>Use bootstrapping to create sampling distributions for the parameters of a generalised linear model.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p> </p> |
| 6 | <p>Use a fitted regression model to answer specific questions about the relationship between the explanatory variables and the response.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p><p><strong style="color: rgb(73, 80, 87);">Solution-Seeking</strong></p><p><strong style="color: rgb(73, 80, 87);">Communication</strong></p> </p> |
| 7 | <p>Explore relationships between variables using appropriate graphical techniques.</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p><p><strong style="color: rgb(73, 80, 87);">Solution-Seeking</strong></p> </p> |
| 8 | <p>Explain the ethical risks of both accurate and inaccurate predictive modelling in society</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p><p><strong style="color: rgb(73, 80, 87);">Ethics and Professionalism</strong></p> </p> |
| 9 | <p>Understand and explain how inference in generalised linear models relies on assumptions about the data-generating process</p> | <p>MSc - Master of Science - Graduate Profile <p><strong style="color: rgb(73, 80, 87);">Knowledge and Practice</strong></p><p><strong style="color: rgb(73, 80, 87);">Critical Thinking</strong></p><p><strong style="color: rgb(73, 80, 87);">Communication</strong></p> </p> |