Graduate Course Directory and Schedules

This course covers an experimental design and statistical analysis of biological/clinical data from various experiments. This course provides not only theoretical aspect of experimental design but also hand-on experience in designing and analyzing experiments. The course begins design principles that include concepts of replication, randomization, blocking, multifactor studies, and confounding. Basic matrix algebra concepts will be explored to establish the basis for linear models. Students, then, are introduced to various experimental designs including analysis of variance (ANOVA) in both single and multi-factorial setting, experiments to study variances, complete/incomplete block designs (CBD), split plot design, repeated measures ANOVA, analysis of covariance (ANOCOVA), response surface design, and diagnosing agreement between the data and model. The course also provides experience in analyzing unbalanced experimental. Computer application is included as part of the course to introduce students to data management, reading output, interpreting and summarizing results.
 
Prerequisite
BSTA 511