Numerical Methods for Chemical Engineering

Are you looking to apply rigorous statistical methods to your chemical engineering challenges? This course provides a foundational understanding of numerical and statistical techniques essential for modern chemical engineering practice. You will gain the ability to apply statistical inference, parameter estimation, and regression analysis to solve complex problems, interpret data, and make informed decisions in your field. What you'll learn: - Understand fundamental probability concepts, including distributions and Bernoulli trials. - Apply Bayesian statistics for parameter estimation and inference. - Implement linear and nonlinear least squares regression for data analysis. - Grasp the principles of Brownian dynamics and stochastic differential equations. - Generate and interpret confidence intervals for model predictions. - Practice applying these methods to simulated chemical engineering scenarios. - Explore modern applications of statistical modeling in chemical process analysis. This course begins with essential statistical definitions and progresses through practical applications, ensuring a solid grasp of the material. It is designed for beginners with no prior background in these specific numerical methods, assuming only basic chemical engineering concepts. Start applying powerful analytical techniques to your chemical engineering work today.