About Data:
The dataset included records of advertising expenditures across TV, Radio, and Newspaper, along with corresponding sales figures, enabling data-driven decision-making in advertising strategies.
Problem Statement:
The project aimed to analyze the impact of advertising channels (TV, Radio, Newspaper) on sales to optimize future advertising strategies.
Solution:
Utilized simple linear regression to establish relationships between advertising expenditures and sales figures, aiming to understand each medium's contribution to sales. The model achieved an impressive R-squared value of 81%, indicating a good fit to the data and robust predictive capability.
Libraries:
Leveraged pandas and numpy for data manipulation and preprocessing, and utilized statsmodels and sklearn for analysis, offering robust functionalities for regression modeling and evaluation.