Part A Simulation and Statistical Programming HT 2019

### Statistical
programming

Part A Simulation and Statistical
Programming has two webpages, one webpage for the Simulation theme
(lectured by Prof Berestycki) and this webpage for the Statistical Programming
theme (which I lecture). Prof Berestycki’s page is the ‘main’ page. Material common to both
themes will appear there (for example, the problem sheets).

### Lectures and
practical sessions

The following lectures and practical
sessions are based on material provided by Prof Evans.

We meet six times, Tuesdays 3-5pm in
weeks 1,2 and 3 and Friday 9-11am in weeks 5,6 and 8. These meetings will start
with a short lecture-style intro to the material, and then we move onto the
computers and do some practical exercises.

Week 1 Slides
& Practical 1
with sample solutions

Week 2 Slides
& Practical 2
with sample solutions and
lecture code

Week 3 Slides
& Practical 3
with sample solutions
and lecture code

Week 5 Slides
& Practical 4
with sample solutions
and lecture code

Week 6 Slides
& Practical 5
with sample solutions

Week 8 Slides
& Practical 6
(MHcode.R)

My old
lecture notes and practical material from 2015 are available here.

### Datasets

Cystic
Fibrosis (cystfibr.txt)

Tetrahymena
Data (hellung.txt)

Japanese
beetle larvae data (beetlelarva.txt)

Speed Data (speed.txt)

Air
Pollution Data (airpol.txt)

Image Data (noisy, true)

### Resources

We will be using the
statistical software package R, which you can get here. Please install it on your own
computer and practice using it as early as possible. You may find it helpful to
bring a laptop to use during lectures, but it is not necessary.

The software
RStudio is also useful.

Here is a R-tutorial
I prepared with questions and answers.
It is a quick reminder of some core R.

*Recommended reading*

W.J. Braun and D
Murdoch, "A First Course in Statistical Programming with R", ISBN
0-521-69424-8

C.P. Robert and G
Casella, ``Introducing Monte Carlo Methods with R'

* *

*Advanced texts*

W. Venables and
B.D. Ripley, “Modern Applied Statistics with S”, ISBN 0- 387-95457-0

** **

"Anyone who
can do solid statistical programming will never miss a meal."

(Prof David Banks
2008)

**Geoff Nicholls /
nicholls@stats.ox.ac.uk**