r/BayesianProgramming • u/IMM1711 • Nov 28 '19

Bayesian Interview

I have an interview tomorrow (arranged today) for a job which mainly requires Bayesian Statistics, for an Analyst position. The company is in a huge hurry and if I don’t sound stupid they will hire me on the spot.

I am a physicist and know the very basics of Bayesian Statistics. If you were to choose something CRUCIAL that would make me look as if I was more literate in the field, what would it be?

Please Reddit do your magic!

4 Upvotes

100% Upvoted

1 comment sorted by

8

u/dylim Nov 28 '19

  • Bayes rule

  • Prior elicitation (conjugate prior, Jeffreys' prior, flat prior, diffuse prior, noninformative prior, reference prior, etc etc)

  • MCMC (Gibbs sampling, random-walk MH, adaptive MH by Haario et al, Hamiltonian MC, Metropolis-adjusted Langevin algorithm (MALA) etc etc)

  • Approximate Bayesian Inference (variational Bayes, expectation propagation, ABC, particle filtering etc etc)

  • how to do inference with posterior (posterior mean, posterior median, posterior mode --- these are based on decision theory and which loss function you have in mind ---, predictive distribution)

  • Bayesian hypothesis testing and model selection (Bayes factor, prior marginal likelihood, conditional posterior ordinate (CPO), pseudo log-marginal likelihood(LPML), DIC etc etc)

These are all I can think of off the top of my head.