Data is precious, and the aims of any good observer or experimentalist should be to make best use of it. To do this requires an understanding of statistics. Most undergraduates regard statistics as a boring necessity. This is entirely understandable, since it is often introduced into undergraduate laboratories in the form of a set of rules which must be followed to calculate and propagate errors. In fact there is much more to the subject than this. Much of the scientific enterprise can be regarded as one of making comparisons between models of reality and the data with which they are tested. Moreover the area is the subject of a lively debate between two schools of thought - Bayesians and frequentists - who disagree about the whole role of probability in the analysis of data. Once one understands this, the subject becomes much more interesting. The main aim of the course is to give you the beginnings of such an understanding, and to help you to apply the tools of statistical analysis in your own research problems. Although the techniques introduced are entirely general, they will be illustrated using examples drawn mostly from the lecturer's own field: astronomy. The course is assessed via a variety of practical analysis exercises which are also mostly astronomical in nature. Some interest and experience in astronomy would therefore help you to connect with these examples. |