Examining the Association of Advertising Spending on Sales

This project investigates the relationship between advertising spending and sales using multiple linear regression. Companies invest in TV, radio, and newspaper advertising to boost sales. This analysis answers:

• Does spending on different advertising channels affect sales?
• Which type of advertising is the most effective?
• Can we predict sales based on advertising spending?

Using the Advertising Spend vs. Sales dataset from Kaggle, we explore the data, fit a regression model, and interpret results

Data Origin and Overview

The dataset used in this project, titled Advertising Spend vs. Sales, originates from Kaggle. Click here to be directed to the kaggle dataset. The dataset contains the following 4 numerical variables (all in thousands of dollars):

• TV: Total Spent on TV advertisements
• Radio: Total Spent on radio advertisements
• Newspaper: Total Spent on newspaper advertisements
• Sales: Total sales

Objective

• Analyze the impact of advertising spend on sales
• Identify which advertising channels significantly predict sales
• Build a multiple linear regression model
• Interpret model coefficients, significance, and predictive ability

Clone the repository

git clone https://github.com/ismahahmed/Advertising-Sales-Regression.git
cd Advertising-Sales-Regression

Install packages

install.packages(c("tidyverse", "broom", "ggplot2", "corrplot"))