Perspectives on Randomness in Statistics

Welcome to the course website for the EDMA PhD course MATH-705, Perspectives on Randomness in Statistics. All relevant information and materials are collected and will be updated on this page.

  • Location: EPFL, CM1 113
  • Time: 10.00 - 11.30
  • Email: tobias [dot] freidling [at] epfl [dot] ch

Description

In this weekly course, we read and discuss different papers that examine how randomness is conceptualized in statistics. There are two presentation formats: (1) We directly examine the reading material and different people can lead the discussion with their comments, questions, and opinions; (2) one of the participants starts the session with a 20-minute presentation introducing the main points and subsequently leading the discussion. See the schedule below for details about the topics and presentations. Regardless of the presentation format, participants are expected to read the material before the session.

Free auditors are always welcome. :)

Schedule

DateTopicPresentation
Sep 23Randomness, PhilosophicallyReading group
Sep 30Randomness, ProbabilisticallyReading group
Oct 07The Bayesian PerspectiveMaxence
Oct 14The Frequentist PerspectiveGellért
Oct 21No course (semester break)
Oct 28Finite and Infinite Populations IEmi
Nov 04No course
Nov 11Finite and Infinite Populations IIGellért
Nov 18Sampling with and without ReplacementTobias
Nov 25Modelling in Survey StatisticsMaxence
Dec 02Finite Populations in Causal InferenceEmi
Dec 09Generalizability and TransportabilityReading group
Dec 16By popular demand

Reading Materials

Randomness, Philosophically

Randomness, Probabilistically

  • Shafer, G. and Vovk, V. (2006) ‘The Sources of Kolmogorov’s Grundbegriffe’, Statistical Science, 21(1), pp. 70–98. link
  • von Mises, R. (1941) ‘On the Foundations of Probability and Statistics’, The Annals of Mathematical Statistics, 12(2), pp. 191–205. link
  • van Lambalgen, M. (1996) ‘Randomness and foundations of probability: von Mises’ axiomatisation of random sequences’, Statistics, probability and game theory. Institute of Mathematical Statistics, pp. 347–368. link

The remaining material will be added soon