Linear Regression Part 2: Parameter Estimation & Statistical Testing | ML Series 03

Continuing our journey into Linear Regression, we dive deep into the mathematical foundations and statistical concepts that make it work!

📚 In this video, we explore:

Least Squares Estimation for parameter calculation
Understanding parameter variance
Statistical testing and model evaluation
Impact of sample size on our models

⏱️ Chapters:

00:00 - Introduction & Overview
02:53 - Parameter Estimation & Least Squares
05:46 - Hypothesis Testing & Model Evaluation
08:00 - Sample Size & Conclusions

🔍 Perfect follow-up to Part 1 where we covered the basics and assumptions of Linear Regression.

📈 Key Topics Covered:

Least Squares method
Parameter variance estimation
Underlying distributions of the parameters
T-statistics and F-statistics
Confidence intervals
Sample size effects


🎓 About the Instructor:

Dr. Muntazir Abidi holds a PhD from Cambridge University and brings extensive experience from Professor Stephen Hawking's research group and the financial sector in London.

👉 Watch Part 1 here:    • Linear Regression Part 1: Basics and ...  
👉 Supervised Learning Intro:    • Understanding AI/ML and Supervised Le...  

💡 Follow for weekly Machine Learning content!

🔗 Learn more about our AI courses and educational services:

Website: https://www.camedventure.com
Email: [email protected]

Follow our Instagram Page for CamEdVenture:   / camedventure  


#MachineLearning #LinearRegression #DataScience #Statistics #MLTutorial #LearnML #LeastSquares #Mathematics #DataAnalysis #MLSeries #CamEdVenture #ArtificialIntelligence #ParameterEstimation #StatisticalTesting #MLMath #DataScience #Education