You visit a local Starbucks to buy a Mocha Frappuccino. Thebarista explains that this blended coffee beverage comes in threesizes and asks if you want a 12-ounce Tall, a 16-ounce Grande, or a24-ounce Venti. The prices are $3.95, $4.45, and $4.95,respectively. There is a clear positive association between thesize of the Mocha Frappuccino and its price.
Plot the data.
Why should you plot size in ounces onthe x axis?
| | Because price is the explanatory variable. |
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| | Because size is the explanatory variable. |
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| | Because size is the response variable. |
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| | Because there is a positive correlation between thevariables. |
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What is the least-squares regression line for predicting the priceusing size? Add the line to your plot. Draw a vertical line fromthe least squares line to each data point. This gives a graphicalpicture of the residuals.
| | yˆ=2.26+0.084xy^=2.26+0.084x |
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| | yˆ=0.0804+2.26xy^=0.0804+2.26x |
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| | yˆ=3.05714+0.08036xy^=3.05714+0.08036x |
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| | yˆ=0.08036+2.6071xy^=0.08036+2.6071x |
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What is the meaning of the middle residual being positive and theother two negative?
| | The 12-ounce and 24-ounce drinks are miss valued and should besold at a higher price. |
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| | The 16-ounce drink is expensive, and the other two sizes arerelatively cheap. |
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| | The 16-ounce drink costs less than the predicted value, and theother two sizes cost more than predicted. |
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| | The 16-ounce drink costs more than the predicted value, and theother two sizes cost less than predicted. |
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