The course focuses on topics such as Linear Models, High Dimensional Data,
Model Diagnostics, Bootstrap and Permutation Tests, Principal Component Analysis, Smoothing
and Cross - Validation. Short notes have been provided which should be considered as a guide or a summary of concepts that may help as we progress with the lectures. More course and learning resource materials will be uploaded on this platform from time to time.

The order in which the topics are presented below may not necessarily be the same order in which
the lecture material will be arranged. You are also advised to read published articles on these
topics to have a feel of the rigour involve in scientific writing and publishing journal articles. Your
homework will be typeset in Latex before submission. Independent work is strongly encouraged.