This repository explores simple linear regression models to analyze the relationship between advertising expenditure and sales. The problem involves understanding the effectiveness of different advertising channels in driving sales and comparing the performance of two models: one using Statsmodels and the other using scikit-learn.
The problem involves analyzing the relationship between advertising expenditure across various channels (TV, radio, newspaper) and sales generated by an advertising firm.
In this repository, we explore simple linear regression models using both Statsmodels and scikit-learn. We aim to understand the effectiveness of different advertising channels in driving sales and compare the performance of the two models in predicting sales based on advertising expenditure.
- We identify the advertising channel with the most significant impact on sales by analyzing the coefficients of the linear regression models.
- Both Statsmodels and scikit-learn models demonstrate reasonable accuracy in predicting sales based on advertising expenditure.
- The analysis provides valuable insights into optimizing advertising strategies for maximizing sales.
- Explore more advanced regression techniques and machine learning algorithms to improve predictive accuracy.
- Conduct further analysis to understand the interaction effects between different advertising channels on sales.
This project was completed as part of the UpGrad Module. We acknowledge the support and guidance provided by the instructor throughout the course.