Credits 
3 credit points 
Audience 
Master Statistical Science 
Lecturer 
Richard Gill. 

Email: gill at math.leidenuniv.nl 
Period 
First half, Autumn semester, 2013 
Hours 2013 
t.b.a. 
Aim 
Introduction to a miscellany of more advanced and/or computer intensive statistical methods, emphasis on "how to do it in R", introduction to "computational statistics" 
Form 
Lectures and (computer) assignments 
Description 
Simulation of random variables 

Sampling distributions and power functions


Visualization, Monte Carlo Integration


Bootstrap 

Numerical algorithms

Resources 
Slides (see below) 

Book: Statistical computing with R, by Maria L. Rizzo, Chapman and Hall. Notice author's book webpage with R scripts download, errata. 

Blackboard: see especially Announcements, Content and Information on Blackboard. It is obligatory to sign up to the course in both uSis and Blackboard. 

Extra handout (others on Blackboard): HMM.pdf 
Assessment 
By weekly reports (2/3 of final grade) and final exam (1/3 of final grade). 
Requirements 
"Statistical computing with R" (which course is actually an introduction to computer programming, and simultaneously an introduction to the R computing language, both with an eye towards applications in statistics) 
Language 
The opensource, free, statistical package R can be downloaded from the Rproject
site www.rproject.org . You might find one of the many more sophisticated graphical user interfaces, such as RStudio, also useful. 
Assignments 
Weekly. Hand in a short report at the beginning of next week (i.e.: before the next lecture!). 