Statistical Science


Modules in Statistical Science for students from other departments

These webpages provide a guide to the modules offered by the Department of Statistical Science that are available to students registered in other UCL departments.

Quick guide to registration

Step 1:Read this guide carefullyEnsure that you have selected a module stated as being available to students from your programme. Availability is dependent on various factors (e.g. capacity), so if a module is indicated as being unavailable to students from your programme then you will not be able to take it (regardless of whether you meet the academic prerequisites).
Step 2:Check for additional registration stepsThe individual module pages within this guide will explain whether students from eligible programmes can simply register for a module on Portico and await a decision, or whether they also need to consult a member of staff in the Department of Statistical Science, to confirm that they meet the academic prerequisites. If consultation is not required, proceed directly to Step 4.
Step 3:Request a staff consultation (if necessary)If indicated as a mandatory component of the registration process for your selected module, you must request a consultation with a member of the teaching staff by completing a consultation request form. The form will ask you to explain how you meet the academic prerequisites for your selected module and upload supporting documentation. It may be possible to confirm your suitability based on this information alone, or you may be invited to attend a follow-up meeting. Please allow one week for a response after submitting your form.
Step 4:Register on PorticoInstructions on Portico module selection are available from the main UCL website.
Step 5:Await a decision

Decisions on teaching department approval will be released from mid-July (continuing students) / mid-September (new students). The Department of Statistical Science will give teaching department approval to as many registrations as possible until a module is at capacity. If a module is oversubscribed, optional registrations will be prioritised over electives.

If you selected a module on Portico that is unavailable to students from your programme (see Step 1), or failed to request a consultation where this was indicated as a requirement (see Steps 2&3), you should expect your selection to be rejected.

Who should (not) use this guide

This guide covers the majority of students registered in other UCL departments. However, it is NOT intended for use by the following groups of students.

  • Students taking compulsory modules in Statistical Science. These students will be registered automatically on Portico for the module(s) in question.
  • Students enrolled on the BSc / MSci Mathematics and Statistical Science (MASS) programmes, for whom separate arrangements are made. These students should instead refer to the module selection information published by the Department of Mathematics.
  • Students enrolled on the Mathematics and Statistics stream of the BSc / MSci Natural Sciences degree programmes, for whom separate arrangements are made. These students should instead refer to the module selection information published on the Natural Sciences website.
  • Students on affiliate programmes who are enrolled at UCL during the autumn term only. None of the modules offered by the Department of Statistical Science are suitable for these students (because some of the formal assessment extends into the second and third terms).
Module types

The modules fall into two categories.

  • Service modules specifically provided for students from other departments.
  • Departmental modules primarily intended for students enrolled on the degree programmes offered by the Department of Statistical Science, but which may also be suitable for students from other departments.

In addition to having taken acceptable prerequiste courses, students from other departments may have to do some preliminary reading for some Departmental modules.

Module availability

The modules fall into two categories.

  • A module may be specified as Optional within a particular programme by formal agreement between the Department of Statistical Science and the relevant parent department. There is generally a streamlined registration process for students from these programmes.
  • Some modules are in principle available as an Elective to students from any UCL programme (at the corresponding level). Such students may need to consult a member of staff in the Department of Statistical Science as part of the registration process, who will determine whether they have the necessary academic prerequisites.

If a module is not designated as Elective in the below list (or does not feature in the list at all), registration attempts from students outside of programmes for which the module is Optional will be unsuccessful.

Teaching arrangements

Details of teaching events and learning resources for each module are available from the UCL Timetable and Moodle. After confirming your selection on Portico, you will be automatically enrolled onto the Moodle course for the module and any required tutorial/workshop allocations will be arranged by a Teaching & Learning Administrator at the beginning of the relevant term. Your tutorial/workshop group will then be accessible from your online timetable. However, it may take one or two working days after selection on Portico before all of these processes are completed. Note also that, once allocated, your tutorial/workshop group will NOT be changed unless you can demonstrate a timetable clash.

Students' attendance at tutorials and workshops will be monitored. Unsatisfactory attendance or an unsatisfactory coursework record will be reported to a student's Programme Tutor.

Intercollegiate study

The modules designated as having "Elective" availability are also available in principle to incoming intercollegiate students. The application process for intercollegiate study is organised centrally at UCL, but the initial step requires students to seek informal approval from the relevant UCL teaching department. To obtain such approval for one of the Elective modules listed below, there is still the standard requirement to consult a member of staff in the Department of Statistical Science, to confirm that the academic prerequisites are met. However, since the online form linked in the quick guide above requires a UCL login, prospective intercollegiate students can instead initiate a consultation by emailing stats.ugt@ucl.ac.uk.

Module list

Click on each module title for more information about availability, academic prerequisites, registration requirements, and for other relevant details.

STAT0002Introduction to Probability and Statistics41DepartmentalOptional
STAT0003Further Probability and Statistics42DepartmentalOptional
STAT0005Probability and Statistics II - Now full for 2024/2561ServiceOptional
STAT0006Regression Modelling51DepartmentalElective
STAT0007Stochastic Processes - Now full for 2024/2562ServiceOptional
STAT0008Statistical Inference71DepartmentalOptional
STAT0010Forecasting6 & 72DepartmentalOptional, Elective
STAT0011Decision and Risk52DepartmentalOptional, Elective
STAT0013Stochastic Methods in Finance - Now full at UG level for 2024/256 & 71DepartmentalOptional, Elective
STAT0015Medical Statistics 272DepartmentalOptional
STAT0018Stochastic Methods in Finance II6 & 72DepartmentalOptional, Elective
STAT0019Bayesian Methods in Health Economics72DepartmentalOptional
STAT0020Quantitative Operational Risk Modelling6 & 72DepartmentalOptional, Elective
STAT0021Introductory Statistical Methods and Computing41 or 2ServiceElective
STAT0022Introductory Statistical Methods41 & 2ServiceOptional
STAT0025Optimisation and Operations Research61DepartmentalElective
STAT0026Statistics for Medical Scientists51 & 2ServiceOptional
STAT0028Statistical Models and Data Analysis71DepartmentalElective
STAT0029Statistical Design of Investigations71DepartmentalOptional
STAT0030Statistical Computing71 & 2DepartmentalOptional
STAT0031Applied Bayesian Methods72DepartmentalOptional, Elective
STAT0032Introduction to Statistical Data Science71DepartmentalOptional
STAT0041Algorithms and Data Structures51DepartmentalElective
STAT0042Statistical Machine Learning6 & 71DepartmentalElective
STAT0043Inference at Scale6 & 72DepartmentalOptional, Elective
STAT0044Computational Statistics72DepartmentalElective
STAT0046Applied Multivariate and High-Dimensional Methods72DepartmentalElective