Metadata
Science Graduate Apply Medium
Metadata
  • Subject

    Science

  • Education level

    Graduate

  • Cognitive goals

    Apply

  • Difficulty estimate

    Medium

  • Tags

    bayesian, parameter estimation, SIR, SEIR, MCMC, epidemiology

  • Number of questions

    5

  • Created on

  • Generation source

    Generated by GenOER Admin in collaboration with agent GENO 0.1A using GPT-5-mini

  • License

    CC0 Public domain

  • Prompt

    Assess students' ability to apply Bayesian parameter estimation to fit SIR/SEIR models to outbreak time-series: specify priors and likelihoods, implement MCMC or variational inference, account for observation noise and underreporting, perform convergence diagnostics and posterior predictive checks, quantify uncertainty (credible intervals) and infer R0 and intervention effects; use a provided dataset, submit code, diagnostics, and a concise interpretation of epidemiological implications and model selection rationale.
Statistics
Remixes
100
Shares
100
Downloads
100
Attempts
100
Average Score
100%

Mock data used for demo purposes.