To predict the sales quantity for an advertising budget of $119,000, we can use a simple linear regression model. Linear regression estimates the relationship between the independent variable (advertising budget) and the dependent variable (sales).

Steps:

1. Identify the independent and dependent variables:

   • Independent variable (X): Advertising budget.
   • Dependent variable (Y): Sales.

2. Use the linear regression equation: $\hat{Y} = \beta_0 + \beta_1 X$ Where:

   • $\hat{Y}$ is the predicted sales.
   • $X$ is the advertising budget.
   • $\beta_0$ is the y-intercept (constant).
   • $\beta_1$ is the slope (rate of change in sales for a unit increase in advertising budget).

I will calculate the regression coefficients and predict the sales for an advertising budget of $119,000. Let me calculate that for you.The predicted sales quantity for an advertising budget of $119,000 is approximately $724,258.

Would you like more details or have any questions?

Here are 5 related questions you might find helpful:

1. How is the slope ($\beta_1$) of a linear regression line calculated?
2. What other methods can be used to predict sales from an advertising budget?
3. How accurate is the linear regression model in this case?
4. What happens if the relationship between advertising and sales is nonlinear?
5. Can we use multiple regression if we have other factors besides advertising?

Tip: Always check the goodness of fit (e.g., $R^2$) when using linear regression to assess how well the model explains the data.