Schedule
aug 27 · review · [slides] [notes] [solutions] fractions, logarithms, and exponents; calculus; matrices; probability theory
sep 03 · ml · [slides] [notes] [solutions] maximum likelihood; invariance principle; predictive distribution
sep 10 · se · [slides] [materials] [notes] [solutions] sampling distribution; parametric bootstrap; variance and standard error; delta method
sep 17 · X · [slides] [materials] [notes] [solutions] adding covariates; logit models; expected value and first difference
sep 24 · {marginaleffects} · [slides] [materials] [notes] [solutions] {marginaleffects}; information criteria; zero inflation
oct 01 · bayes · [slides] [materials] [notes] [solutions] Bayesian inference; rejection sampling; a Bayesian invariance property; censoring; duration models Due Oct. 1: prospectus for research paper.
oct 08 · mcmc · [slides] [materials] [notes] [exerices + solutions] Metropolis algorithm; HMC + Stan and its R ecosystem
oct 15 · midterm exam [comments]
oct 22 · hierarchical models · [slides] [notes] [exercises] Due: (1) first draft of research paper due and (2) initial outline of take-home workshop handout.
oct 29 · irt · [slides] [notes] [exercises] Due: (1) peer-review memo and (2) first drafts of all workshop materials.
nov 05 · mrp · [slides] [notes] [exercises] Due: workshop rehearsal
nov 12 · case study: fowler et al. (2023) · [slides] [notes] [exercises]
nov 19 · case study: fariss (2014) · [slides] [notes] [exercises]
nov 26 · thanksgiving break Due by Tuesday: (1) second draft of research paper and (2) hold workshop.
dec 03 · wrap · [slides] [notes] [exercises] Poster presentation this week.
dec 10 · final exam
Due: Final draft of research paper.