Covers: theory of Variance-Covariance Matrix

- What is the variance covariance matrix and how does it describe the underlying distribution of data?

Watch the whole video, Brandon does a great job of describing how to calculate the variance-covariance matrix, how to read one, and how to apply it real life contexts.

Fail to play? Open the link directly: https://www.youtube.com/watch?v=locZabK4Als

Brandon Foltz

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

Previewing stream ** Math and Foundations**

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