# Untitled

**Source**: https://teaching.scss.tcd.ie/wp-json/wp/v2/module/2196
**Parent**: https://teaching.scss.tcd.ie/module/stu34506-modern-statistical-methods-ii-2/

{"id":2196,"date":"2020-11-12T11:08:04","date\_gmt":"2020-11-12T10:08:04","guid":{"rendered":"https:\/\/teaching.scss.tcd.ie\/?post\_type=module&p=2196"},"modified":"2025-06-09T11:14:16","modified\_gmt":"2025-06-09T10:14:16","slug":"stu34506-modern-statistical-methods-ii-2","status":"publish","type":"module","link":"https:\/\/teaching.scss.tcd.ie\/module\/stu34506-modern-statistical-methods-ii-2\/","title":{"rendered":"STU34506 – Modern Statistical Methods II"},"content":{"rendered":"\n

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| **Module Code<\/strong><\/td> STU34506<\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **Module Name<\/strong> <\/td> Modern Statistical Methods II<\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **ECTS Weighting [**[1]<\/strong><\/a><\/strong><\/td> 5 ECTS <\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **Semester taught<\/strong><\/td> Semester 2<\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **Module Coordinator\/s <\/strong><\/td> Alessio Benavoli<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nModule Learning Outcomes <\/h2>\n\n\n\n **Module Learning Outcomes <\/strong><\/p>\n\n\n\n On successful completion of this module**, <\/strong>students will have the ability to<\/p>\n\n\n\n LO1. Devise suitable simulation methods for generating random numbers from a given probability distribution.<\/p>\n\n\n\n LO2. Use the sampled random numbers to estimate quantities of interest or evaluate integrals.<\/p>\n\n\n\n LO3. Assess the quality of the generated sample via diagnostic tools.<\/p>\n\n\n\n LO4. Choose appropriate Monte Carlo sampling algorithms.<\/p>\n\n\n\n LO5. Apply stochastic simulation methods in practice.<\/p>\n\n\n\n LO6. Modify the methods for a specific application.<\/p>\n\n\n\nModule Content<\/h2>\n\n\n\n Monte Carlo methods are stochastic simulation-based algorithms designed to compute approximated solutions to problems where exact solutions are intractable and take exponential time to compute.  The scope of this module is to review fundamental aspects in Monte Carlo simulation.<\/p>\n\n\n\n Specific topics addressed in this module include: \u2022 Random variable generation: transformation methods, accept-reject methods \u2022 Monte Carlo integration and importance sampling \u2022 Markov Chains Markov Chain Monte Carlo Methods, like Metropolis-Hastings and Gibbs sampler \u2022 Sequential Monte Carlo Methods \u2022 Theoretical aspects such as convergence and performance analysis \u2022 Inference in Probabilistic programming through MCMC<\/p>\n\n\n\n It also gives an opportunity for students to apply these tools to practical problems in statistical learning, data science, machine learning, and other areas, using the R programming language.<\/p>\n\n\n\n  <\/p>\n\n\n\nTeaching and learning Methods <\/h2>\n\n\n\n Live lecturers and QAs with accompanying lecture notes and handouts, available through Blackboard. Blackboard discussion forums.<\/p>\n\n\n\nAssessment Details <\/h2>\n\n\n\n  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **Assessment Component<\/strong><\/td> **Brief Description<\/strong> <\/td> **Learning Outcomes Addressed<\/strong><\/td> **% of total<\/strong><\/td> **Week set<\/strong><\/td> **Week Due<\/strong><\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Examination<\/td> 2 hours in-person exam<\/td> LO1, LO2, LO3, LO4, LO5, LO6<\/td> 70%<\/td> N\/A<\/td> N\/A<\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Coursework<\/td> Project<\/td> LO1, LO2, LO3, LO4, LO5, LO6<\/td> 30%<\/td> 8<\/td> 11<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nReassessment Details<\/h2>\n\n\n\n \u00a0In-person Examination (2 hours, 100%)\u00a0<\/p>\n\n\n\nContact Hours and Indicative Student Workload<\/h2>\n\n\n\n  |  |  |  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | **Contact Hours (scheduled hours per student over full module), broken down by<\/strong>: <\/td> 33 **hours<\/strong><\/td><\/tr>|  |  |  |  |  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Lecture<\/td> 29<\/td><\/tr>| Tutorial or seminar<\/td> 4<\/td><\/tr>|  |  |  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | --- | --- | | **Independent study (outside scheduled contact hours), broken down by:<\/strong><\/td> 82 **hours<\/strong><\/td><\/tr>|  |  |  |  |  |  | | --- | --- | --- | --- | --- | --- | | Preparation for classes and review of material (including preparation for examination, if applicable<\/td> 42<\/td><\/tr>|  |  |  |  | | --- | --- | --- | --- | | completion of assessments (including examination, if applicable)<\/td> 40<\/td><\/tr>|  |  | | --- | --- | | **Total Hours<\/strong><\/td> 115 **hours<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\nRecommended Reading List<\/h2>\n\n\n\n Robert, Christian, and George Casella. “Monte Carlo statistical methods”. Springer Science & Business Media, 2013. Robert, Christian , and George Casella. “Introducing Monte Carlo methods with R”. Vol. 18. New York: Springer, 2010.<\/p>\n\n\n\nModule Pre-requisites <\/h2>\n\n\n\n **Prerequisite modules:<\/strong> STU23501, STU22005<\/p>\n\n\n\n **Other\/alternative non-module prerequisites:<\/strong> Basic R programming and knowledge of linear algebra will be useful.<\/p>\n\n\n\nModule Co-requisites <\/h2>\n\n\n\n None<\/p>\n\n\n\nModule Website<\/h2>\n\n\n\n [Blackboard<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" (Semester 2, 5 ECTS)<\/p>\n","protected":false},"author":104,"menu\_order":0,"template":"","meta":[],"module\_category":[],"class\_list":["post-2196","module","type-module","status-publish","hentry"],"\_links":{"self":[{"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/module\/2196","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/module"}],"about":[{"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/types\/module"}],"author":[{"embeddable":true,"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/users\/104"}],"wp:attachment":[{"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/media?parent=2196"}],"wp:term":[{"taxonomy":"module\_category","embeddable":true,"href":"https:\/\/teaching.scss.tcd.ie\/wp-json\/wp\/v2\/module\_category?post=2196"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}](https://teaching.scss.tcd.ie/wp-json/wp/v2/module/\"https:\/\/tcd.blackboard.com\/webapps\/login\/\")****** |** | | | | |** |** | | | | |** |** | | | | | | | | | | | | |** |** |** |** |** |** |**** |** | |** | |**](https://teaching.scss.tcd.ie/wp-json/wp/v2/module/\"#_ftn1\")** | |** | |** |