This course provides an introduction to probability and parametric inference. Topics include: random variables, standard distributions, the law of large numbers, the central limit theorem, likelihood-based estimation, sampling distributions and hypothesis testing, as well as an introduction to Bayesian methods. Some assignments may involve computation using the R programming language.Outcome 1: Students will be able to manipulate random variables and their distributions using differential and integral calculus.Outcome 2: Students will be able to derive properties of standard probability.Outcome 3: Students will be able to derive maximum likelihood estimators for standard probability distributions and discuss their properties.
Probability Models and Inference
Course Number
STSCI
3080