\[( 5.6, 8.8 ), ( 6.3, 12.4 ), ( 7, 14.8 ), ( 7.7, 18.2 ), ( 8.4, 20.8 )\]
x <- c(5.6, 6.3, 7, 7.7, 8.4)
y <- c(8.8, 12.4, 14.8, 18.2, 20.8)
regression <- data.frame (x,y)
# Round to the nearest hundredth.
round(coef(lm(y ~ x, regression)), 2)
## (Intercept) x
## -14.80 4.26
Answer: The equation of the regression line is \(y = -14.8 + 4.26x\)
\[f ( x, y ) = 24x - 6xy^2 - 8y^3\]
Answer:
Partial derivatives:
\(f_x = 24 - 6y^2\)
\(f_y = -12xy -24y^2\)
Set \(f_x\) to 0 and solve for \(y\):
\(24 - 6_y^2 = 0\)
\(24 = 6_y^2\)
\(4 = y^2\)
\(±2 = y\)
Set \(f_y\) to 0 and substitute \(y = 2\):
\(−12xy − 24y^2 = 0\)
\(xy + 2y^2 = 0\)
\(x(2) + 2(2)^2 = 0\)
\(2_x + 8 = 0\)
\(2X = -8\)
\(x = -4\)
Substitute \(y = -2\):
\(x(-2) + 2(-2)^2 = 0\)
\(-2x + 8 = 0\)
\(−2x = −8\)
\(x = 4\)
Substitute \((x,y)\) for \(z\):
Substitute \((-4,2)\) and \((4,-2)\):
\(z = 24(-4) - 6(-4)(2)^2 - 8(2)^3\)
\(z = -96 + 96 - 64\)
\(z = -64\)
\(z = 24(4) - 6(4)(-2)^2 - 8(-2)^3\)
\(z = 96 - 96 + 64\)
\(z = 64\)
The critical points are \((-4, 2, -64)\) and \((4, -2, 64)\)
Now use the Second Derivative test to determine if the points are minimum, maximum, or saddle.
\(f_{xx} = 0\)
\(f_{yy} = -12x - 48y\)
\(f_{xy} = - 12y\)
\(D = f_{xx}(x,y) * f_{yy}(x,y) - f_{xy}^2(x,y)\)
\(D = 0(x,y) * (-12x - 48y(x,y)) - (- 12y)^2(x,y)\)
\(D = 0 - 144y^2(x,y)\)
\(D = -144y^2(x,y)\)
Answer: As per the Second Derivative Test, \(D(x,y) < 0\) for both \((-4,2,-64)\) and \((4,-2,64)\), so therefore both critical points are saddle points.
Step 1. Find the revenue function \(R ( x, y )\).
Answer:
The revenue function is unit cost multiplied by units sold for the house/name brand and can be defined as follows:
\[R(x,y) = x(81 - 21x + 17y) + y(40 + 11x -23y)\]
Step 2. What is the revenue if she sells the "house" brand for $2.30 and the "name" brand for $4.10?
Answer:
We can find the revenue by substituting \(x\) in the above function with the price of the house brand ($2.30), and \(y\) with the price of the name brand ($4.10).
x <- 2.3
y <- 4.1
revenue <- (x * (81 - (21 * x) + (17 * y))) + (y * (40 + (11 * x) - (23 * y)))
revenue
## [1] 116.62
The revenue is $116.62.
If \(x + y = 96\), then \(y = 96 - x\).
\[C(x,y) = \frac{1}{6}x^2 + \frac{1}{6}y^2 + 7x + 25y + 700\] \[C(x,y) = \frac{1}{6}x^2 + \frac{1}{6}(96-x)^2 + 7x + 25(96-x) + 700\] \[C(x,y) = \frac{1}{6}x^2 + \frac{1}{6}(9216 - 192x + x^2) + 7x + 2400 - 25x + 700\] \[C(x,y) = \frac{1}{6}x^2 + 1536 - 32x + \frac{x^2}{6} + 7x + 2400 - 25x + 700\] \[C(x,y) = \frac{1}{3}x^2 - 50x + 4636\] \[C' = \frac{2}{3}x - 50\] \[0 = \frac{2}{3}x - 50\] \[50 = \frac{2}{3}x\] \[75 = x\]
Answer: 75 units should be produced in Los Angeles and the remaining 21 units should be produced in Denver to minimize the total weekly cost.
\[\iint_{R}(e^8x + 3y) \ dA; R: 2 \leq x \leq 4 \ and \ 2 \leq y \leq 4\]
Answer:
\[\int_2^4\int_2^4(e^{8x + 3y})dx dy\] \[int_2^4(1/8)(e^{16} - 1)e^{3y + 16} dy\] \[e^{16} - 1) / 24 e^{3y + 16} + C\] \[(e^{44} - e^{28}) / 24 - (e^{38} - e^{22}) / 24\] \[(1 / 24)(e^{22} - e^{28} - e^{38} + e^{44})\]