Main group 1

Course literature

Lecture materials will be provided

recommended reading

• Sainudiin, Raazesh; Lee, Dominic; Nussbaum, Michael, Background in Probability Theory I & Inference Theory I,, Matematiska institutionen m.fl., 2020, https://github.com/lamastex/computational-statistical-experiments/blob/master/matlab/csebook/PrStEl.pdf
• Wasserman, Larry, All of statistics: a concise course in statistical inference, New York, Springer, cop. 2004 (available in UU Library)
• Luc Devroye; Gábor Lugosi; László Györfi, A Probabilistic Theory of Pattern Recognition, Springer, 1996

Lecture notes will be communicated in the lectures and problem sessions as there is no appropriate book for the course. We will quickly build from measure-theoretic probability and concentration inequalities towards theoretical foundations in data science in the course.