We are continuously striving to improve our teaching programmes based on student and SSLC feedback, new developments in academia and industry and module leader input. Changes are normally agreed in consultation with the SSLC (Student Staff Liaison Committee). Below is a summary of key improvements and changes we are introducing for 26/27.
If you have suggestions on how we can further improve our programme or concerns about the changes, please do get in touch by filling out this feedback form (for current students) or by e-mailing . Alternatively you may share your feedback with one of the student representatives of the SSLC.
We are continuing to provide academic support to first and second year students via the SMASH initiative. Do come along to SMASH to be supported by a fantastic team of tutors and the opportunity to learn with fellow students!
ST119 Probability 2: University mathematics focusses much more on conceptual understanding than numerical calculations. Therefore, in consultation with the SLLC we have reduced the number of exams where calculators are needed. From 26/27 onwards calculators are no longer permitted for the ST119 exam.
ST121 Statistical Laboratory: This module offered to external students provides, amongst other topics, an introduction to simple linear regression. We added an additional learning outcome to acknowledge that this module prepares external students to take second year modules in linear statistical modelling (ST231 Linear Statistical Modelling with R).
ST227 Stochastic Processes: We have updated the study time description to clarify that there are four tutorials. These take place fortnightly, but there is no tutorial in Week 1 to avoid clashes with January exams. We also removed some minor topics from the outline syllabus and the explicit mention of random walks in the module aims. Random walks are a special case of Markov chains, they are still discussed as examples of Markov chains and so the material you learn in this module continues to provide you with the essential background on random walks.
ST229 Probability for Mathematics and Statistics: This module will continue to offer a 10% coursework component. However, to reduce the number of compulsory submission deadlines, prepare students better for the exam and alleviate concerns about misuse of AI, the material of the coursework will now be assessed via class tests. We consulted on this approach with the SSLC who were in support. You will have 3 class tests spread over the term.
ST230 Mathematical Statistics: As for ST229, you will have 3 class tests spread over the term.
ST232 Introduction to Mathematical Statistics: This module for external students now also has a finalist version (ST352 Introduction to Mathematical Statistics (for Finalists)). We revised the description of the learning outcomes to make clearer the distinction between ST232 and ST352. We also made it clearer in the assessment description that the in-term assessments are in form of multiple choice quizzes.
ST236 Python for data-analytic tasks: To balance modules with a large coursework component across the two teaching terms, we have moved ST236 to Term 1.
ST237 Visualisation and Communication of Data: To reduce the assignment load and alleviate concerns about the misuse of AI we have replaced one assignment by a class test and slightly redistributed the weighting across the various assessment components.
Calculators: In consultation with the SSLC, we have reduced the number of exams where calculators are needed. From 26/27 onwards calculators are no longer permitted for the exam of ST227 and ST228.
We started the redesign of our machine learning modules to provide a more systematic structure for students who would like to learn more about machine learning and big data. For 26/27 we revised ST340 Programming for Data Science which now runs as ST340 Fundamentals of Machine Learning and provides an introduction to the theoretical foundations and key algorithms in machine learning. The module will run in Term 1 and leads to ST349 Machine Learning Frameworks and ST420 Statistical Learning and Big Data, both of which continue to run in Term 2.
We are now offering an "advanced topic version" of ST346 Generalised Linear Models for Regression and Classification, namely ST426 Generalised Linear Models with Advanced Topics.
ST347 Actuarial Models and Life Contingencies: This is a module running over two terms. We made the assessment more balanced across the two terms, each term now has a class test, a computer-based assessment and an exam (Term 1 is examined in January, Term 2 in the summer exam period). To support students in preparing for the assessments we have added four additional tutorials in Term 1.
ST301/ST413 Bayesian Statistics and Decision Theory (With Advanced Topics): We slightly updated the syllabus and made minor tweaks to the learning outcomes to accommodate the updated syllabus.
ST344 Professional Practice of Data Analysis: We added a description of the subject-specific and transferable skills you will gain from the module.
ST352 Introduction to Mathematical Statistics (for Finalists): This module offered to third year external students replaces ST232 Introduction to Mathematical Statistics (for Finalists). Being a third year level module helps finalists meet the requirements for their third year.
In consultation with the SSLC, we have reduced the number of exams where calculators are needed. From 26/27 onwards calculators are no longer permitted for the ST323/ST412 and the ST333/ST406 exams.
ST961 Statistical Methods and Practice: To allow more time to focus on the foundational material, we reduced overlap with optional modules by removing a learning outcome that referred to computational statistics methods such as rejection and importance sampling. For those interested in the subject, approaches to computational statistics are extensively covered in the optional module ST407 Monte Carlo Methods.
ST962 Advanced Topics in Statistics and Probability: To manage the workload of the module, the assessment is now based on two rather than all case studies. This will allow students to focus on the case studies of most interest to them.
ST909 Applications of Stochastic Calculus in Finance: We updated the learning outcomes to make them clearer and more accessible to students and clarify expectations for the module assessments.
ST980 Dissertation: While planning your research is still an important part of your dissertation, you are no longer required to submit a research management plan with your dissertation.
