HT 2017 - Computational Statistics SB1b/SM2

Lecturers: Prof Fran├žois Caron, Dr Jennifer Rogers
Class tutors: Prof Fran├žois Caron, Dr Jennifer Rogers
Teaching Assistants: Giuseppe di Benedetto, Fadhel Ayed

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


Undergraduate revision class on May 17 at 2pm, LG01.
09-05: Details of revisions classes
13-04: Specimen questions



Tuesday 12:00-13:00
LG.01, 24-29 Saint-Giles'

Friday 12:00-13:00
LG.01, 24-29 Saint-Giles'
Practicals MSc

Friday 14:00-16:00
LG.02, 24-29 Saint-Giles'
Practicals Undergrad
Wednesday 15:00-16:30
LG.02, 24-29 Saint-Giles'
Problem classes MSc

Thursday 13:30-14:30
LG.01 24-29 Saint-Giles'
Problem classes Undergrad

Thursday 9-10, 14:30-15:30 or 17-18
LG.05 24-29 Saint-Giles'



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', and send the R code by email, in a single well-commented R-script to Giuseppe Di Benedetto <> (Thursday 9:00 or 14:30 class) or Fadhel Ayed <> (Thursday 17:00 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.

Specimen questions on Hidden Markov models and revisions

Specimen questions on Hidden Markov models

Revision class for undergraduate students: May 17, 2pm LG01. We will cover the above specimen questions on HMM + 2015 past paper Q5(a)(i-iii), (iv) first sentence + 2016 past paper Q5(a).
Consultation for undergraduate students: May 24, 2-3pm, LG01.

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: 08 Feb. 2017