Question

You visit a local Starbucks to buy a Mocha Frappuccino. The barista explains that this blended coffee beverage comes in three sizes and asks if you want a 12-ounce Tall, a 16-ounce Grande, or a 24-ounce Venti. The prices are $3.95, $4.45, and $4.95, respectively. There is a clear positive association between the size of the Mocha Frappuccino and its price.

Plot the data.
Why should you plot size in ounces on the x axis?

Because price is the explanatory variable.

Because size is the explanatory variable.

Because size is the response variable.

Because there is a positive correlation between the variables.

What is the least-squares regression line for predicting the price using size? Add the line to your plot. Draw a vertical line from the least squares line to each data point. This gives a graphical picture of the residuals.

yˆ=2.26+0.084xy^=2.26+0.084x

yˆ=0.0804+2.26xy^=0.0804+2.26x

yˆ=3.05714+0.08036xy^=3.05714+0.08036x

yˆ=0.08036+2.6071xy^=0.08036+2.6071x

What is the meaning of the middle residual being positive and the other two negative?

The 12-ounce and 24-ounce drinks are miss valued and should be sold at a higher price.

The 16-ounce drink is expensive, and the other two sizes are relatively cheap.

The 16-ounce drink costs less than the predicted value, and the other two sizes cost more than predicted.

The 16-ounce drink costs more than the predicted value, and the other two sizes cost less than predicted.

Answer 1

(A) because size is explanatory variable