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Consultations and revision classes

PLEASE NOTE THAT TIMES MAY CHANGE AT SHORT NOTICE, PLEASE CHECK BACK CLOSER TO THE TIME

A12 Simulation and Statistical Programming

  • Revision class, Tuesday week 3, 3pm-4pm, LG.01 (Professor Berestycki). 2018 exam paper.
  • Revision class, Tuesday week 4, 2pm-3pm, LG.01 (Professor Nicholls). Past papers from 2015-2017, focusing on R-related questions.
  • Consultation session, Wednesday week 4, 10am-11am, LG.05 (Professor Berestycki).
  • Revision class/Consultation session, Tuesday week 6, 2pm-3pm, LG.01 (Professor Nicholls). Past paper from 2018 and question and answer session on any topic.

SB1.1 Applied Statistics

  • Revision class, Friday week 2, 11am-12.30pm, LG.01 (Linear Models – Dr Laws). The revision class will cover SB1 question 1 from each of the years 2016, 2017 and 2018.
  • Consultation session, Friday week 3, 11am-12pm, LG.04 (Linear Models – Dr Laws).
  • Revision class, Friday week 4, 11am-12.30pm, LG.01 (GLM – Professor Rogers).
  • Consultation session, Friday week 5, 11am-12pm, LG.04 (GLM – Professor Rogers).

SB1.2 Computational Statistics

SB2.1 Foundations of Statistical Inference

  • Revision class, Thursday week 2, 2pm-3pm; Wednesday week 4, 2pm-3pm,  LG.01 (Professor Rousseau).
  • Consultation session, Wednesday week 3, 12pm-1pm, LG.01 (Professor Rousseau).
  • Consultation session, Thursday week 4, 4pm-5pm, LG.04 (Emilia Pompe). Please send in questions beforehand.
  • Revision class, Tuesday week 5, 9am-10am, LG.01 (Professor Rousseau).

SB2.2 Statistical Machine Learning

  • Revision class, Wednesday week 2, 9am-10am, LG.01 (Professor Palamara).
  • Consultation session, Tuesday week 3, 3pm-4pm, LG.04 (Anthony Caterini).
  • Revision class, Tuesday week 4, 10am-11am, LG.01 (Brian Zhang).
  • Consultation session, Tuesday week 5, 10am-11am, LG.04 (Brian Zhang).

SB3.1 Applied Probability

  • Consultation session, Wednesday week 2, 9am-10.30am, LG.05 (Dr Winkel).
  • Consultation session, Monday week 3, 9am-10am, LG.04 (Dr Winkel).
  • Revision classes, Tuesday week 5, 10am-12pm, LG.01 (Professor Berestycki). 2018 exam paper.
  • Consultation session, Wednesday week 5, 9am-10.30am, LG.03 (Dr Winkel).
  • Revision class, Thursday week 5, 10am-12pm, LG.01 (Alexander Homer). The class will cover the 2017 exam paper.
  • Consultation session, Friday week 5, 10.30am-12.30am, LG.03 (Dr Stephenson).

SB3.2 Statistical Lifetime Models

  • Consultation sessions, Wednesday week 3, 9.30am-11.15am and Thursday week 5, 11am-12.45pm, Worcester College room 16.4 (Professor Steinsaltz). Time will be split into 15 minute slots, with a maximum of three students per slot. Instructions on how to sign up can be found on the course website: http://www.steinsaltz.me.uk/SB3b/SB3b.html
  • Revision class, Monday week 4, 9.30am-11am, LG.01 (Professor Steinsaltz). The class will cover a set of questions from past papers and sample questions given on the course website.

SB4.1 Actuarial Science

  • Revision class/consultation session, Monday week 2, 2pm-4pm, LG.01 (Mr Green). Revision class followed by consultation.
  • Revision class/consultation session, Friday week 3, 9am-10am in LG.01 and 10am-11am in LG.03 (Mr Green). Revision class followed by consultation.
  • Revision class/consultation session, Thursday week 4, 10-11am in LG.03 and 11am-12pm in LG.01 (Mr Green). Consultation followed by revision class.

More information can be found on the Weblearn site.

SC1 Stochastic Models in Mathematical Genetics

  • Consultation session, Tuesday week 2, 3pm-4pm, LG.05 (Professor Myers).
  • Consultation session, Tuesday week 4, 3pm-4pm, LG.05 (Leo Speidel and Chris Gill)
  • Revision Class, Tuesday week 5, 3pm-4.30pm, LG.01, (Professor Myers). The class will cover questions from the 2017 paper.

SC2 Probability and Statistics for Network Analysis

  • Revision class, Wednesday week 2, 3pm-5pm; Tuesday week 4, 3pm-5pm, LG.01 (Professor Reinert and Professor Cucuringu). The first 90 minutes will go over exam questions (2017 and 2018 exam papers), the last 30 minutes there will be time for individual questions.

SC4 Advanced Topics in Statistical Machine Learning

  • Revision classes, Tuesday weeks 3 and 5, 2pm-3pm, LG.01 (Professor Sejdinovic). Revision classes will cover SC4 2017 and SC4 2018 exam respectively.
  • Consultation sessions, Monday weeks 3 and 5, 10am-11am, LG.05 (Jean-François Ton and Tomas Vaskevicius). Please send in any questions before the session.

SC5 Advanced Simulation Methods

  • Revision class/consultation (first hour will be a revision class and second hour the consultation), Wednesday week 2, 10am-12pm, LG.01 (Professor Deligiannidis).
  • Revision class/consultation (first hour will be a revision class and second hour the consultation), Wednesday week 4, 9.30am-11.30am, LG.01 (Dr Paulin).

The revision classes will cover last year’s paper and one question from the year before.

SC6 Graphical Models

  • Consultation session, Friday week 2, 11am-12pm, LG.04 (Bohao Yao).
  • Revision class, Thursday week 3, 10am-11am, LG.03 (Professor Evans).
  • Consultation session, Friday week 4, 10am-11am, LG.05 (Sebastian Schmon).
  • Revision class, Wednesday week 5, 11am-12pm, LG.03 (Professor Evans).

SC7 Bayes Methods

  • Revision classes, Friday week 2, 9.30am-11am and Friday week 3, 10am-11am, (Professor Nicholls). Week 2 – 2017 MSc and Part C papers, week 3 – 2018 MSc and Part C papers.
  • Consultations, Thursday and Friday week 4, 10am-11am, LG.05 (Thurs)/LG.03 (Fri) (Professor Nicholls).

SC9 Interacting Particle Systems

  • Revision class, Thursday week 3, 12pm-1.30pm, LG.03 (James Ayre).

SC10 Algorithmic Foundations of Learning

  • Revision class, Monday weeks 2 and 3, 9am-10.30am, LG.o1 (Professor Rebeschini). The revision classes will cover Mock Exams 1 and 2 respectively.
  • Consultation session, Monday week 4, 9am-10am, LG.05 (Professor Rebeschini). Please submit questions before the session.

For the complete information visit: http://www.stats.ox.ac.uk/~rebeschi/teaching/AFoL/18/

Link to the Mathematical Institute consultation and revision classes.