Advanced presentation of statistical methods for comparing populations and estimating and testing associations between variables. Topics include point estimation; confidence intervals; hypothesis testing; ANOVA models for 1, 2, and k way classifications; multiple comparisons; chi-square test of homogeneity; Fisher's exact test; McNemar's test; measures of association, including odds ratio, relative risks, Mantel-Haenszel tests of association, and standardized rates; repeated measures ANOVA; simple regression; and correlation.
Covers regression analysis and introduction to linear models. Topics include multiple regression, analysis of covariance, least square means, logistic regression, and non-linear regression. The course includes a one-hour computer lab and emphasizes hands-on applications to datasets from the health sciences.