Course Title: Basics of Statistical Inference

Course ID: BST222 (Full Term Course)

Topics to be covered:
Fundamental ideas of probability, various statistical models (normal, binomial, exponential, Poisson, geometric, uniform, Cauchy, and others), sample and population moments, finite and approximate sampling distributions, the central limit theorem and applications, point and interval estimation, hypothesis testing, permutation tests, computational inference using bootstrapping and related methods, nonparametric statistics, and applications to linear and logistic regression. Properties and comparison of estimators, hypothesis tests, and confidence intervals will be an important part of the course.

Prerequisites: BST210 or BST213Formerly BIO222

Prior math/stat knowledge: Background in algebra and calculus required.

Computing: Stata, SAS, R will be used in lecture and lab sessions.