Consider a multiple regression analysis conducted to investigate the relationship between a firm’s sales (dependent variable) and various independent variables including advertising spend, market size, and number of stores. The regression equation is given as:

$$ Sales = \beta_0 + \beta_1(Advertising) + \beta_2(Market\ Size) + \beta_3(Number\ of\ Stores) + \epsilon $$

Where:

• \( \beta_0 \) is the intercept.
• \( \beta_1, \beta_2, \beta_3 \) are the coefficients representing the change in sales for a unit change in their respective independent variables.

Suppose the estimated coefficients are:

• \( \hat{\beta_1} = 2.5 \)
• \( \hat{\beta_2} = 1.8 \)
• \( \hat{\beta_3} = 5.0 \)

The coefficients imply that: