Price-demand. A company manufactures memory chips for microcomputers. Its marketing research department, using statistical techniques, collected the data shown in Table 8 , where p is the wholesale price per chip at which x million chips can be sold. Using special analytical techniques ( regression analysis ), an analyst produced the following price demand function to model the data: p x = 75 − 3 x 1 ≤ x ≤ 20 (a) Plot the data points in Table 8 , and sketch a graph of the price-demand function in the same coordinate system . (b) What would be the estimated price per chip for a demand of 7 million chips? For a demand of 11 million chips?
Price-demand. A company manufactures memory chips for microcomputers. Its marketing research department, using statistical techniques, collected the data shown in Table 8 , where p is the wholesale price per chip at which x million chips can be sold. Using special analytical techniques ( regression analysis ), an analyst produced the following price demand function to model the data: p x = 75 − 3 x 1 ≤ x ≤ 20 (a) Plot the data points in Table 8 , and sketch a graph of the price-demand function in the same coordinate system . (b) What would be the estimated price per chip for a demand of 7 million chips? For a demand of 11 million chips?
Price-demand. A company manufactures memory chips for microcomputers. Its marketing research department, using statistical techniques, collected the data shown in Table
8
, where
p
is the wholesale price per chip at which
x
million chips can be sold. Using special analytical techniques (regression analysis), an analyst produced the following price demand function to model the data:
p
x
=
75
−
3
x
1
≤
x
≤
20
(a) Plot the data points in Table
8
, and sketch a graph of the price-demand function in the same coordinate system.
(b) What would be the estimated price per chip for a demand of
7
million chips? For a demand of
11
million chips?
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.
Homework Let X1, X2, Xn be a random sample from f(x;0) where
f(x; 0) = (-), 0 < x < ∞,0 € R
Using Basu's theorem, show that Y = min{X} and Z =Σ(XY) are indep.
-
Homework Let X1, X2, Xn be a random sample from f(x; 0) where
f(x; 0) = e−(2-0), 0 < x < ∞,0 € R
Using Basu's theorem, show that Y = min{X} and Z =Σ(XY) are indep.
rmine the immediate settlement for points A and B shown in
figure below knowing that Aq,-200kN/m², E-20000kN/m², u=0.5, Depth
of foundation (DF-0), thickness of layer below footing (H)=20m.
4m
B
2m
2m
A
2m
+
2m
4m
Chapter 2 Solutions
Finite Mathematics for Business, Economics, Life Sciences and Social Sciences
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