Question

Grant Corporation manufactures a drink bottle, model CL24. During 2017, Grant produced 220,000 bottles at a total cost of $990,000. Young Corporation has offered to supply as many bottles as Grant wants at a cost of $4.40 per bottle. Grant anticipates needing 235,000 bottles each year for the next few years.

What other information would you need to be confident that the equation in accurately predicts the cost of manufacturing drink bottles? (Select all that apply.)
A. How good is the goodness of fit? That is, how well does the estimated line fit the data?
B. Does the slope of the regression line indicate that a strong relationship exists between manufacturing costs and the number of drink bottles produced?
C. Can Grant's competitors manufacture drink bottles at a cost less than Grant?
D. Is the relationship between total manufacturing costs and quantity of drink bottles economically plausible?

Answer 1

To accurately predict the cost of manufacturing drink bottles, it is important to assess the goodness of fit, evaluate the slope of the regression line, and consider the economic plausibility of the relationship between manufacturing costs and quantity.

Step-by-step explanation:

In order to be confident that the equation accurately predicts the cost of manufacturing drink bottles, the following information is needed:

1. How good is the goodness of fit? This refers to how well the estimated line fits the data. It is important to assess the accuracy of the predicted costs based on the relationship between production quantity and manufacturing costs.
2. Does the slope of the regression line indicate a strong relationship? The slope helps determine the strength of the relationship between manufacturing costs and the number of drink bottles produced. A steep slope suggests a significant impact of quantity on costs.
3. Is the relationship between total manufacturing costs and quantity economically plausible? The plausibility of the relationship helps ensure that the predicted costs are reasonable and aligned with economic factors.