Simple Linear Regression

Image from Humas Indonesia

Goal

To perform simple linear regression modeling step by step using Python.

Objectives

1. Import the necessary data and libraries.
2. Check the assumptions of the linear regression model, such as normality and linearity.
3. Define the independent variable (X) and the dependent variable (y).
4. Split the data into training and testing sets.
5. Fit a simple linear regression model.
6. Evaluate the model by checking metrics such as MSE and R-Square.
7. Create a visualization comparing actual data and predicted results.
8. Draw conclusions.

Dataset

This is a synthetic dataset generated using AI, consisting of 100 rows and two columns: Calorie Intake and Body Weight.

Tools

1. Python Programming Language.
2. Jupyter Notebook.

Documentation

1. Dataset
2. Python Notebook