Handbook

This course introduces modern nonparametric techniques for statistical analysis. Nonparametric methods are often said to “let the data speak for itself”, as they do not require the analyst to make any strong assumptions about the process which generated the data. This is in contrast with classical statistical procedures which are essentially parametric: they assume that the data follows a prescribed model defined in terms of a small number of parameters. This course is an elective course for the Master and/or Honours degree of Statistics programs. As it gives another insight into statistical theory, it can be thought of as an interesting complement to most of the other statistics courses which the student may have taken in their program. The key topics are introduced during weekly lectures.