Estimating Sales Revenue Using Regression Coefficients

A financial analyst is examining the relationship between various factors affecting the annual sales revenue ($Y$) of a retail store. To quantify this relationship, they decide to conduct a multiple regression analysis that includes three independent variables: advertising expenditure ($X_1$), number of store promotions ($X_2$), and average store foot traffic ($X_3$). The regression equation is given by:

$$ Y = eta_0 + eta_1X_1 + eta_2X_2 + eta_3X_3 + ext{error} $$

The analyst obtains the following coefficients from the regression output:

• Intercept ($eta_0$): 25000
• Advertising Coefficient ($eta_1$): 5
• Promotions Coefficient ($eta_2$): 300
• Foot Traffic Coefficient ($eta_3$): 150

If the store invests $1000 in advertising, implements 10 promotions, and attracts 2000 customers, what is the estimated annual sales revenue?