BSTA 523 Design of Experiments: Statistical Principles of Research Design & Analysis

Credits: 3
This course covers experimental design and statistical analysis of biological/clinical data from various experiments. This course provides not only the theoretical aspect of experimental design but also hands-on experience in designing and analyzing experiments. The course begins with a discussion of 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 settings, experiments to study variances, complete/incomplete block designs (CBD), split plot designs, repeated measures ANOVA, analysis of covariance (ANCOVA), response surface designs, and diagnosing agreement between the data and model. The course also provides experience in analyzing unbalanced experimental data. Computer application is included as part of the course to introduce students to data management, reading output, along with interpreting and summarizing results.

Graded: A-F
May be taken only once for credit