Linear Regression

This repository will cover various topics related to linear regression:

• Simple and multiple linear regression with scikit-learn
• Simple and multiple linear regression with statsmodels
• Limitations of Linear Regression
• Interacting with Categorical Variables

Set up your Environment

Please make sure you have forked the repo and set up a new virtual environment. For this purpose you can use the following commands:

The added requirements file contains all libraries and dependencies we need to execute the linear regression notebooks.

macOS type the following commands :

• Install the virtual environment and the required packages by following commands:

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/bin/activate
  pip install --upgrade pip
  pip install -r requirements.txt

WindowsOS type the following commands :

• Install the virtual environment and the required packages by following commands.

  For PowerShell CLI :

  pyenv local 3.11.3
  python -m venv .venv
  .venv\Scripts\Activate.ps1
  python -m pip install --upgrade pip
  pip install -r requirements.txt

  For Git-Bash CLI :

  pyenv local 3.11.3
  python -m venv .venv
  source .venv/Scripts/activate
  python -m pip install --upgrade pip
  pip install -r requirements.txt
  

Data

The datasets for the notebooks are stored in the data.zip folder. To unzip the data folder directly in the terminal run

unzip data.zip

Objectives

At the end of this repo you should

• know how to use scikit-learn to train a linear regression model.
• have an understanding of the usage and limitations of linear regression.
• know how to use the statsmodels library for OLS.