The course introduces contemporary computational methods and tools for designing experiments and analysis of data, frequency distribution and probability concepts. The course covers statistical inference, empirical models, strategies for efficient experimentation and their applications in chemical and biomedical engineering analysis. Statistical methods including error analysis, curve fitting and regression, analysis of variance, confidence intervals, hypothesis testing, and control charts are covered. In the laboratory, students apply analyses to contemporary engineering research and design problems. Prerequisites: MATH 132 (With C or higher grade). (F)