4.0

Average Course Rating

Presents use of confidence intervals and and hypothesis tests to draw scientific statistical inferences from public health data. Introduces generalized linear models, including linear regression and logististic regression models. Develops unadjusted analyses and analyses adjusted for possible confounders. Outlines methods for model building, fitting and checking assumptions. Focuses on the accurate statement of the scientific question, appropriate choice of generalized linear model, and correct interpretation of the estimated regression coefficients and confidence intervals to address the question.