Examining the Association of Advertising Spending on Sales

Does spending on different advertisement types have an effect on sales? Companies invest in different types of advertising, such as TV, radio, and newspapers advertisement in order to increase sales. This project examines whether spending on these advertisements are associated with a change in sales and identifies which type of spending is most effective. This project explores advertising data and uses it to calculate a least squares regression equation that predicts Sales (in thousands) based on advertising spending on TV, newspapers, and radio. We will formally test whether the set of these predictors is associated with total sales at the $\alpha$ = 0.05 significance level. Furthermore, we will analyze the significance of the model by summarizing the contribution of each type of advertising separately, again at the $\alpha$ = 0.05 significance level.

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