Dr Matthew Aldridge
Tutor information is taken from the Module Catalogue
You can do well on this module by reading the notes and watching the videos, attending the lectures and tutorials, and working on the problem sheets and R worksheets, without needing to do any further reading beyond this. However, students can benefit from optional extra background reading or an alternative view on the material, especially in the parts of the module on probability.
For exploratory data analysis, you can stick to Wikipedia, but if you really want a book, I'd recommend:
– GM Clarke and D Cooke, A Basic Course in Statistics, 5th edition, Edward Arnold, 2004.
For the probability section, any book with a title like "Introduction to Probability" would do. Some of my favourites are:
– JK Blitzstein and J Hwang, Introduction to Probability, 2nd edition, CRC Press, 2019.
– G Grimmett and D Welsh, Probability: An Introduction, 2nd edition, Oxford University Press, 2014.
– SM Ross, A First Course in Probability, 10th edition, Pearson, 2020.
– RL Scheaffer and LJ Young, Introduction to Probability and Its Applications, 3rd edition, Cengage, 2010.
– D Stirzaker, Elementary Probability, 2nd edition, Cambridge University Press, 2003.
On Bayesian statistics, I recommend:
– JV Stone, Bayes' Rule: A Tutorial Introduction to Bayesian Analysis, Sebtel Press, 2013.
For R, there are many excellent resources online, and Google is your friend for finding them.
(For all these books I've listed the newest editions, but older editions are usually fine too.)
This list was last updated on 11/09/2021