Covers: theory of Linear Regression

- The theoretical underpinnings of linear regression.

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

Trevor Hastie, Robert Tibshirani, Jerome Friedman

Nour Fahmy**Total time needed: **~50 minutes

- Learning Objectives
- Learn about linear regression.
- Potential Use Cases
- Linear regression is a fundamental regression technique.
- Target Audience
- INTERMEDIATE

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

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