To discover what and how environmental or man-made conditions alter the outcomes, a study needs to be carefully planned so that resulting data are relevant, informative, and efficient, ensuring that the cost is minimized, bias controled, and relevant information maximized. This course intends to be an interdisciplanary overview of design and analysis of experimental and observational studies in health research and practice. Emphasis is on the application of statistical principles to the design of a study. Implementation and analysis of a study are also discussed. Examples are drawn from clinical trials, health outcome evaluation, laboratory testing, as well as engineering.
Statistical software is used for data analysis.
Use of statistical software is expected to analyze data from studies of intermediate complexity using such methods as ananlysis of variance and covariance. Sample size and statistical power.