BOOK_CHAPTERLinear regression: An Intro

Covers: theory of Linear Regression
Estimated time needed: 30 minutes
Questions this item adddesses:
  • The theoretical underpinnings of linear regression.
How to use this item?

Read section 3.1, it gives a comprehensive view of how linear regression works.

Author(s) / creator(s) / reference(s)
Trevor Hastie, Robert Tibshirani, Jerome Friedman

Linear Regression

Nour FahmyTotal time needed: ~50 minutes
Learning Objectives
Learn about linear regression.
Potential Use Cases
Linear regression is a fundamental regression technique.
Target Audience
Go through the following annotated items in order:
BOOK_CHAPTER 1. Linear regression: An Intro
  • The theoretical underpinnings of linear regression.
30 minutes
BOOK_CHAPTER 2. Classes of Restricted Estimators
  • What is an estimator? Enumerate the different ways one can estimate data.
10 minutes
VIDEO 3. Variance-Covariance Matrix: An In Depth Tutorial
  • What is the variance covariance matrix and how does it describe the underlying distribution of data?
20 minutes
ARTICLE 4. F-Statistic: A quick refresher
  • How do you determine the F-statistic and why do we use it?
10 minutes
ARTICLE 5. Scikit-learn implementation of Linear Regression
  • Implementing linear regression in scikit learn.
10 minutes

Concepts Convered