Statistical Methods and Experimental Design in Bioprocessing

Catalog description

The proposed course provides students with a foundational understanding of statistical principles and data analysis techniques tailored to bioprocessing applications. Emphasizing practical use of statistical software (JMP), the course covers hypothesis testing, ANOVA, regression analysis, and core Design of Experiments (DoE) methodologies including full factorial, fractional factorial, and response surface designs such as Box-Behnken. Students will also be introduced to multivariate data analysis tools such as Principal Component Analysis (PCA) and Partial Least Squares (PLS) to address complex datasets. Through case studies and bioprocess-specific examples, students will gain hands-on experience in interpreting results, translating data into actionable insights, and effectively communicating findings to scientific teams in industrial settings.