HT 2019 - Computational Statistics SB1.2/SM2

Lecturers: Prof Geoff Nicholls (lectures 1-7), Prof François Caron (lectures 8-13)
Class tutors: Prof François Caron, Giuseppe di Benedetto, Fadhel Ayed
Teaching Assistants: Giuseppe di Benedetto, Fadhel Ayed, Jingyue Lu
Practical demonstrator: Dominic Richards

You will find on this webpage the material for the second half of the course. The material regarding the first part is available from Geoff Nicholls' webpage.

News





Timetable


Lectures, classes and practicals take place in the department of statistics, 24-29 Saint-Giles'.

WeekLectures

Tuesday 09:00-10:00
LG.01
Lectures

Thursday 11:00-12:00
LG.01
Practicals MSc

Friday 11:00-13:00
LG.02
Practicals Undergrad
(assessed)
Wednesday 15:00-16:30
LG.02
Problem classes MSc

Friday 14:00-15:00
LG.01
Problem classes Undergrad
Thursday 16:45-17:45
Friday 10-11, 11-12, 12-13
LG.04
1XX
2XX
3XXXXX
4XXX

5XXX
X
6XXX

7X

XX
8
XXX

Lectures



Practicals


Undergraduate students
There are two assessed practicals for undergraduate students in week 4 and 8. The student submission deadlines are:
MSc students
There are two non-assessed practicals for MSc students in week 3 and week 6, and one week-long assessed practical in week 1 TT. The student submission deadline for this assessed practical is Monday 10:00 TT week 2.


Problem classes


Undergraduate students
Please hand in the solutions to the problem sheets by Tuesday 12:00 before the class, at the department of statistics, 24-29 Saint-Giles' (write your name and the TA's name on the script), and send the R code by email, in a single well-commented R-script to Giuseppe Di Benedetto <giuseppe.dibenedetto@spc.ox.ac.uk> (Friday 10am class), Jingyue Lu <jingyue.lu@spc.ox.ac.uk> (Thursday 16:45 and Friday 11 classes) or Fadhel Ayed <fadhel.ayed@some.ox.ac.uk> (Friday 12:00 class). Class allocation details are on Minerva (accessible from Oxford University network).
MSc students
There is no marking of problem sheets for MSc students. Please complete the problem sheets before the class. Solutions will be available on Weblearn.

Specimen questions on Hidden Markov models and revisions



Specimen questions on Hidden Markov models

Revision class for undergraduate students: Tuesday 7 May (week 2) and 21 May (week 4), 11-12am, LG01. We will cover the above specimen questions on HMM + 2015 past paper Q5(a)(i-iii) + 2016 past paper Q5(a) + 2017 past paper Q3. MSc students are welcome to attend the class.

Please see Geoff Nicholls webpage for information on the revision class and consultation session on the first part of the course.


Background reading


L. Wasserman. All of Statistics. A concise course in Statistical Inference. Chapter 8. Sptringer, 2010.
L. Wasserman. All of Nonparametric Statistics, Springer, 2005.
B. Efron, R.J. Tibshirani. An Introduction to the Bootstrap. Chapman and Hall, 1993.
B. Efron. Bootstrap methods: Another Look at the Jackknife. Annals of Statistics, Vol. 7(1), pp. 1-26, 1979. [pdf]
K.P. Murphy. Machine Learning. A probabilistic perspective. Chapters 17 and 18. The MIT Press, 2012.
D. Barber. Bayesian reasoning and machine learning. Cambridge University Press, 2012.

Last update: 30 April 2019