The following table shows worldwide sales of a certain type of cell phone and their average selling prices in 2012 and 2013.
| Year | 2012 | 2013 |
|---|---|---|
| Selling Price ($) | 395 | 335 |
| Sales (millions) | 672 | 1,020 |
(a)
Use the data to obtain a linear demand function for this type of cell phone. (Let p be the price, and let q be the demand).
q(p) =
Use your demand equation to predict sales if the price is lowered to $285.
million phones
(b)
Fill in the blank.
For every $1 increase in price, sales of this type of cell phone decrease by million units.
he following table shows soybean production, in millions of tons, as a function of the cultivated area, in millions of acres.
| Area (millions of acres) | 25 | 30 | 32 | 40 | 52 |
| Production (millions of tons) |
25 | 35 | 40 | 50 | 70 |
Show a plot of the points together with the regression line.
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(b) Interpret the slope of the regression line.
Production ---Select--- increases decreases by million tons of soybeans per million acres of cultivated land.
Use technology to compute the sum-of-squares error (SSE) for the given set of data and linear models.
(2, 4), (6, 8), (8, 12), (10, 0)
(a)
y = ?0.4x + 7
SSE =
(b)
y = ?0.7x + 6
SSE =
Indicate which linear model gives the better fit.
y = ?0.4x + 7
y = ?0.7x + 6