STAT 335: Data Simulation and Analysis

Course description

Uses Monte Carlo simulations to understand operating characteristics of a statistical method. Approximates bias and variance for point estimation, coverage probability for interval estimation, and Type I error rate and statistical power for hypothesis testing. Studies the impact of model misspecification and the importance of adjusting confounding variables in observational studies. Introduces how to build (parameterize) a statistical model to address a research question of interest. (Prereq: MATH 320 or STAT 250 or STAT 100 or BUS 204 with a C- or better)

Units:4