Essentials of Math Modeling - Introduction to Regression and Statistical Ideas

Dive into the sixth session of the "Essentials of Math Modeling" series, focusing on regression and statistical concepts. Explore linear regression, least squares estimation, and data transformations through MATLAB examples and practical applications. Learn how to evaluate model performance, conduct sensitivity analysis, and apply these techniques to real-world scenarios like SIR models. Engage in problem-solving sessions that reinforce concepts from previous sessions and provide hands-on experience with sample problems. Access supplementary materials, including handbooks, code, and slides, to enhance your learning experience throughout this comprehensive introduction to regression and statistical ideas in mathematical modeling.

Reminders
Linear Regression
Linear Model
Least Squares Estimation
MATLAB Examples
How Do We Measure How Good Our Line Is?
How Much Variation is Explained...
Useful Example to Keep in Mind
Data Looking Non Linear?
Data Transformations
Sensitivity Analysis
Case Study: SIR Models
Absolute and Relative Error
Problem Solving Session: Recap From Session 5
Problem Solving Session: Overview of This Session
Problem Solving Session: Sample1
Problem Solving Session: Sample2