A model-based approach to modern methods in data analysis. Comparison of statistical approaches including frequentist, likelihood, and Bayesian techniques. Methods for simulating data, estimating parameters for single variable models, constructing multivariate and hierarchical models, model comparison using information criteria, and model suitability using posterior predictive analysis.
4
UnitsLetter
Grading1
PasstimeNone
Level LimitLetters and science
College