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Chemical Engineering - CHEG 632

Process Optimization and Quality Improvement

• Be able to develop MATLAB programs including loops, conditionals, and input/output.
• Calculate basic statistics including estimators for the mean and variance of a population.
• Test hypotheses using student’s t-test.
• Find parameters for simple models using univariate linear regression.
• Find parameters for multivariate linear regression models.
• Find parameters using matrix techniques for non-linear regression.
• Find parameters using the Nelder-Mead (simplex) method for non-linear regression.
• Develop and plot joint-confidence regions for linear and non-linear regression parameters.
• Solve constrained optimization problems by linear programming.
• Solve constrained optimization problems by non-linear programming.
• Develop and interpret Shewhart Charts for univariate statistical process control.
• Develop and interpret the Hotelling’s T-Square statistic for multivariate statistical process control.