This is a home page for a course
16 lectures to second year Cambridge mathematics students
over 8 weeks.
Current students please note that the course schedule has changed since these notes were written in 2007. What is here is still relevant, but the new schedule covers the general linear model, and Gauss-Markov theorem, which is not covered in these notes.
There are three examples sheets; each is a pdf file of 2 pages. The
questions appear in the same order as topics are covered in lectures
you will find a recommendation on the sheet concerning the work you
do for your supervisions. Viewing and printing is identical as for the
You may like to look at comments which a supervisor wrote
the attempts that his students made on the examples sheets. He notes
things that they did wrong and where they had difficultiess. You could
usefully use these comments as hints and try to do
better than these students.
There is another file of overheads that I used with lectures. This is
mostly larger scale displays of information that is in the notes.
However, there are scatter plots and regression lines with
confidence bands for which there was not enough space to reproduce in
D. A. Berry and B. W. Lindgren,
Statistics, Theory and Methods, Duxbury
1995, ISBN 0-534-50479-5.
G. Casella and J. O. Berger,
Statistical Inference, 2nd Edition,
Brooks Cole, 2001, ISBN 0-534-24312-6.
M. H. De Groot, Probability
and Statistics, 3rd edition,
Addison-Wesley, 2001, ISBN 0-201-52488-0.
W. Mendenhall, R. L. Scheaffer and D. D.
Wackerly, Mathematical Statistics with
Press, 6th Edition, 2002, ISBN 0-534-37741-6.
J. A. Rice, Mathematical
Statistics and Data Analysis, 2nd edition, Duxbury Press,
1994, ISBN 0-534-20934-3.
G. W. Snedecor, W. G. Cochran,
Iowa State University Press, 8th Edition, 1989, ISBN 0-813-81561-4.
There are courses in Part II that build on what students learn in this
In Part IIA there is Computational Statistics and
In Part IIB there is Statistical Inference.
Other items of interest
Chance News reviews current issues in the news that use probability or statistical concepts.
Rate Your Risk Quiz.
E.g. What is the risk of your being wiped out (with nearly
everybody else) next year by a catastrophic comet, meteor, or asteroid
One in 750,000? One in 20,000? One in 15,000,000?
Wikipedai entriies of some famous statisticians: Bayes
(Bayesian inference), Gosset
(Student's t-distribution), Neyman
(Neyman-Pearson test), Pearson
An interesting item about
speed cameras and whether or not they actually reduce the