This course on Introduction to Regression and Statistical Ideas aims to teach students the fundamentals of linear regression, least squares estimation, data transformations, sensitivity analysis, and error measurement techniques. The course utilizes MATLAB examples and real-world case studies to illustrate these concepts. The teaching method includes theoretical explanations, practical examples, and problem-solving sessions. This course is intended for students and individuals interested in gaining a foundational understanding of regression analysis and statistical modeling.
Essentials of Math Modeling - Introduction to Regression and Statistical Ideas
Society for Industrial and Applied Mathematics via YouTube
Overview
Syllabus
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
Taught by
Society for Industrial and Applied Mathematics
