Price-demand. A company manufactures notebook computers. Its marketing research department, using statistical techniques, collected the data shown in Table 9 , where p is the wholesale price per computer at which x thousand computers can be sold. Using special analytical techniques ( regression analysis ), an analyst produced the following price-demand function to model the data: p x = 2000 − 60 x 1 ≤ x ≤ 25 (a) Plot the data points in Table 9 , and sketch a graph of the price-demand function in the same coordinate system . (b) What would be the estimated price per computer for a demand of 11 , 000 computers? For a demand of 18 , 000 computers?
Price-demand. A company manufactures notebook computers. Its marketing research department, using statistical techniques, collected the data shown in Table 9 , where p is the wholesale price per computer at which x thousand computers can be sold. Using special analytical techniques ( regression analysis ), an analyst produced the following price-demand function to model the data: p x = 2000 − 60 x 1 ≤ x ≤ 25 (a) Plot the data points in Table 9 , and sketch a graph of the price-demand function in the same coordinate system . (b) What would be the estimated price per computer for a demand of 11 , 000 computers? For a demand of 18 , 000 computers?
Price-demand. A company manufactures notebook computers. Its marketing research department, using statistical techniques, collected the data shown in Table
9
, where
p
is the wholesale price per computer at which
x
thousand computers can be sold. Using special analytical techniques (regression analysis), an analyst produced the following price-demand function to model the data:
p
x
=
2000
−
60
x
1
≤
x
≤
25
(a) Plot the data points in Table
9
, and sketch a graph of the price-demand function in the same coordinate system.
(b) What would be the estimated price per computer for a demand of
11
,
000
computers? For a demand of
18
,
000
computers?
Definition Definition Statistical method that estimates the relationship between a dependent variable and one or more independent variables. In regression analysis, dependent variables are called outcome variables and independent variables are called predictors.
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