`second year statistics students' is rather imprecise, but I will guess
these are undergraduate statistics majors. However, the book by Nolan &
Speed listed in the R FAQ would seem to be at about that level and is
rather close to your description.
@Book{Nolan.Speed.00,
author = {Deborah Nolan and Terry Speed},
title = {Stat Labs. Mathematical Statistics Through Applications},
publisher = {Springer},
year = 2000,
address = {New York},
ISBN = "0-387-98974-9",
}
I've also used examples from
@Book{Ramsey.Schafer.02,
author = {Fred L. Ramsey and Daniel W. Schafer},
title = {The Statistical Sleuth. A Course in Methods of Data Analysis},
publisher = {Duxbury Press},
year = 2002,
edition = "Second",
address = {Belmont, CA},
ISBN = "0-534-38670-9",
}
and
@Book{Fox.02,
author = {John Fox},
title = {A {R} and {S-PLUS} Companion to Applied Regression},
publisher = {Sage Publications},
year = 2002,
address = {Thousand Oaks, CA},
ISBN = "0-7619-2280-6",
}
in courses to graduates based on case studies.
It depends what you mean by `R programming', too. Almost all the
statistics our third-year students (let alone second-year) know can be
done by direct calls to existing R code. (The third years use R as from
last year, and this allows topics such as robust estimation and smoothing
to be covered.)
On Wed, 13 Oct 2004, allan clark wrote:
> hi all
>
> i need some advice. i am a university lecturer and will be teaching a R
> programming course next year. the course will be taught to second year
> statistics students. the aim is to introduce them to programming. the
> emphasis will be on solving real life consulting projects by using R. i
> must still develop the course but if anyone has any suggestions on
> possible content and interesting data sets to explore, please email. if
> any lecturers are offering similar courses could you please send me a
> course outline- some notes if at all possible. references will also be a
> big help. i will appreciate any comments.
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595