This class provides a calculus-based introduction to inferential statistics. Basic concepts of random sampling and statistics including confidence intervals, bias, the method of moments, percentile matching, and sampling distribution estimators will be covered. Additional topics include hypothesis testing using concepts such as the t-test, Chi-square test, goodness-of-fit test, and the Neyman-Pearson Lemma; maximum likelihood estimators; Bayes estimators; sufficient and robust statistics; information criteria; and an introduction to inference on linear models.
Apply to this course