points_df <- data.frame(x = c(5.6, 6.3, 7, 7.7, 8.4), y = c(8.8, 12.4, 14.8, 18.2, 20.8))
linear_model <- lm(y ~ x, data = points_df)
linear_model
##
## Call:
## lm(formula = y ~ x, data = points_df)
##
## Coefficients:
## (Intercept) x
## -14.800 4.257
The equation of the regression line is \(y=-14.80+4.26x\).
Find partial derivatives & critical points: \[ f_x(x,y)=24-6y^2\\ f_y(x,y)=-12xy-24y^2\\ 24-6y^2=0\\ y^2=4\\ y=\pm2\\ -12xy-24y^2=0\\ \text{Let} \space y=2\\ -12x(2)-24(2)^2=0\\ -24x-96=0\\ x=-4\\ \text{Let} \space y=-2\\ -12x(-2)-24(-2)^2=0\\ 24x-96=0\\ x=4\\ f(-4,2)=24(-4)-6(-4)(2)^2-8(2)^3\\ f(-4,2)=-64\\ f(4,-2)=24(4)-6(4)(-2)^2-8(-2)^3\\ f(4,-2)=64\\ \{(-4,2,-64),(4,-2,64)\} \] The function has critical points at (-4,2,-64) and (4,-2,64). Applying the second derivative test will confirm what type(s) of critical points they are.
\[ f_x(x,y)=24-6y^2\\ f_{xx}(x,y)=0\\ f_{xy}(x,y)=-12y\\ \]
Since \(f_{xx}(x,y)=0\), we need only calculate \(f_{xy}(x,y)\) for each critical point to determine if \(D\) is negative or zero (it cannot be positive, given that \(D=f_{xx}f_{yy}-f_{xy}^2\), and the first product will be zero.)
\[ f_{xy}(x,y)=-12y\\ f_{xy}(-4,2)=-12(2)\\ f_{xy}(-4,2)=-24\\ \]
Since \(f_{xy}(-4,2)\) is non-zero, \(D<0\), and \(f\) has a saddle point at \((-4,2,-64)\).
\[ f_{xy}(x,y)=-12y\\ f_{xy}(4,-2)=-12(-2)\\ f_{xy}(4,-2)=24\\ \] Since \(f_{xy}(4,-2)\) is also non-zero, \(D<0\), and \(f\) has another saddle point at \((4,-2,64)\).
In sum, there are no local minima or maxima, and two saddle points: \((-4,2,-64)\), \((4,-2,64)\).
Step 1. Find the revenue function \(R(x,y)\).
\[ R(x,y)=x(81-21x+17y)+y(40+11x-23y)\\ R(x,y)=81x-21x^2+17xy+40y+11xy-23y^2\\ R(x,y)=-21x^2+81x+28xy+40y-23y^2\\ \]
Step 2. What is the revenue if she sells the “house” brand for $2.30 and the “name” brand for $4.10?
\[ x=2.30 \space \text{and} \space y=4.10\\ R(2.3,4.1)=-21(2.3)^2+81(2.3)+28(2.3)(4.1)+40(4.1)-23(4.1)^2\\ R(2.3,4.1)=116.62\\ \] The revenue would be $116.62.
\[ C(x,y)= \frac{1}{6}x^2+\frac{1}{6}y^2+7x+25y+700\\ x+y=96\\ x=96-y\\ C(y)= \frac{1}{6}(96-y)^2+\frac{1}{6}y^2+7(96-y)+25y+700\\ C(y)=\frac{1}{6}(9216-192y+y^2)+\frac{1}{6}y^2+672-7y+25y+700\\ C(y)=\frac{1}{3}y^2-14y+2908\\ C'=\frac{2}{3}y-14\\ \frac{2}{3}y-14=0\\ y=21\\ x=75\\ \] 75 units should be produced in Los Angeles and 21 in Denver.
We can check by comparing surrounding values, which confirms that (75,21,2761) is at least a relative minimum: \[ C(75,21)= \frac{1}{6}(75)^2+\frac{1}{6}(21)^2+7(75)+25(21)+700\\ C(75,21)=2761\\ C(76,20)= \frac{1}{6}(76)^2+\frac{1}{6}(20)^2+7(76)+25(20)+700\\ C(76,20)= 2761.33\\ C(74,22)= \frac{1}{6}(74)^2+\frac{1}{6}(22)^2+7(74)+25(22)+700\\ C(74,22)= 2761.33\\ \]
1/6*75^2+1/6*21^2+7*75+25*21+700
## [1] 2761
1/6*76^2+1/6*20^2+7*76+25*20+700
## [1] 2761.333
1/6*74^2+1/6*22^2+7*74+25*22+700
## [1] 2761.333
\[ \int\int e^{8x+3y}dA;R:2\leq x\leq4\space \text{and} \space 2\leq y\leq4\\ \int_2^4\int_2^4 e^{8x+3y} \space dy \space dx\\ \] First we evaluate the integral with respect to \(y\) using substitution: \[ u=8x+3y\\ du=3dy\\ \int_2^4 e^{8x+3y}\space dy\\ \frac{1}{3}\int_2^4 e^u\space du\\ \frac{1}{3}(e^{8x+3(4)}-e^{8x+3(2)})\\ \frac{1}{3}(e^{8x+12}-e^{8x+6})\\ \]
Then we evalaute the integral with respect to \(x\) using substitution: \[ \int_2^4 \frac{1}{3}(e^{8x+12}-e^{8x+6})\space dx\\ v=8x+6\\ dv=8dx\\ \frac{1}{3}\cdot\frac{1}{8}\int_2^4 (e^{v+6}-e^{v})\space dv\\ \frac{1}{24} ((e^{8(4)+12}-e^{8(4)+6})-(e^{8(2)+12}-e^{8(2)+6}))\\ \frac{1}{24}((e^{44}-e^{38})-(e^{28}-e^{22}))\\ \frac{1}{24}(e^{44}+e^{22}-e^{38}-e^{28})\\ \]
\(\int\int e^{8x+3y}dA\) on the region \(R:2\leq x\leq4\space \text{and} \space 2\leq y\leq4\) is equal to \(\frac{1}{24}(e^{44}+e^{22}-e^{38}-e^{28})\).