Graduate Course 2020 part 2

Posted on 30th January 2020

The 2nd part of my talk to postgraduate students is all about statistics, particularly hypothesis testing, and why I like Bayesian approaches. As the room allocated was long and thin with whiteboards only on the long walls, I decided that a chalk-and-talk would just lead to neck ache in my audience.

So I want with a beamer talk (pdf of slides) which inevitably lead to me finishing early. I guess no-one minded this.

A mini-bibliography:

  • I still really enjoy my undergraduate lecture notes curtesy of Prof. Richard Weber (I feel old to see that Prof Weber is now retired...)
  • Rice, "Mathematical Statistics And Data Analysis" which said lecture notes follow moderately closely. Amazon link. Also available in the UCLAN library.
  • A wonderful book is MacKay, Information Theory, Inference, and Learning Algorithms. Available in electronic format for free.
  • A more straight-up introduction to Bayesian thought is Sivia and Skilling, "Data Analysis: A Bayesian Tutorial". Amazon link. This book blends some philosophical thoughts (but not overly heavy) with practical and interesting advanced statistics. I believe it's available online from one of the online libraries UCLAN subscribes to (and/or is in the library).
  • A more heavy-weight alternative is Bayesian Data Analysis, Third Edition by the gang of six. Amazon link.
  • A bed-time book is the excellent Nate Silver's book "The signal and the noise". Amazon link. Everyone should read this.

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