Lesson 4: Inference, Regression Foundations, and ML Connections
Lesson Overview
Develop practical capability in inference, regression foundations, and ml connections as part of the Essential Mathematics and Statistics for Machine Learning with MATLAB learning path.
Topics Covered
Confidence intervals and sampling uncertainty
Hypothesis testing and p-values
Simple linear regression
Classification boundaries and probability scores
Bias, variance, underfitting, and overfitting
Mathematical review through a MATLAB mini-project
Practical Activity
Build a guided MATLAB exercise covering confidence intervals and sampling uncertainty.
Apply hypothesis testing and p-values to a practical engineering or data scenario.
Validate results and troubleshoot an issue involving mathematical review through a matlab mini-project.
Key Takeaways
Explain and apply confidence intervals and sampling uncertainty.
Use simple linear regression in a structured workflow.
Validate outputs with plots, metrics, tests, or simulation evidence.
