Find the equation of the regression line for the given points. Round any final values to the nearest hundredth, if necessary. ( 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)
df <- data.frame(x, y)
df
## x y
## 1 5.6 8.8
## 2 6.3 12.4
## 3 7.0 14.8
## 4 7.7 18.2
## 5 8.4 20.8
reg_model <- lm(y~x, data=df)
reg_model
##
## Call:
## lm(formula = y ~ x, data = df)
##
## Coefficients:
## (Intercept) x
## -14.800 4.257
plot(x,y, xlab="", ylab="")
abline(reg_model)
lines(c(5,9), -14.8+4.257*c(5,9), col="green")
Find all local maxima, local minima, and saddle points for the function given below. Write your answer(s) in the form ( x, y, z ). Separate multiple points with a comma.
\[ f(x, y) = 24x - 6xy^2 -8y^3 \]
To all local maxima, local minima, and saddle points for the function, we have to first calculate the Determinant:
Finding Partial Derivatives:
\[ f(x, y) = 24x - 6xy^2 -8y^3 \]
\[ fx = \frac{\partial f}{\partial x}=24 - 6y^2 \]
\[ fy = \frac{\partial f}{\partial y}=12xy - 24y^2 \]
Finding Critical Points:
\[ fx = \frac{\partial f}{\partial x}=24 - 6y^2 = 0\]
\[ 6y^2 = 24\]
\[ y^2 = 4\]
\[ y = \pm 2\]
Substituting the values to solve for x
\[ \frac{\partial f}{\partial y}=12xy - 24y^2=0 \]
\[ xy + 2y^2=0 \]
\[ y(x + 2y)=0 \]
When \[ y=2; 2(x+2*2)=0 \]
\[ 2x+8=0 \]
\[ x=-4 \]
When \[ y=-2; -2(x+2*(-2))=0 \]
\[ -2x+8=0 \]
\[ x=4\]
There are two critical points at (−4,2) and (4,−2)
At (−4,2)
\[ z=24(-4)-6(-4)2^2-8(2)^3=-64\]
and at (4,−2)
\[ z=24(4)-6(4)(-2)^2-8(-2)^3=-64\]
two critical points are (−4,2,−64) and (4,−2,64), but to find out if they are minima, maxima or saddle points, we need to find the determinant, D.
Finding the Determinant
\[ fxx =0 \]
\[ fyy =-12x-48y \]
\[ fxy =-12y \]
Now \[ fxxfyy-f^2xy=-(-12y)^2 =-144y^2 \]
D(x,y)<0 for all (x,y), On the basis of the Second Derivative Test, any critical point is a saddle point.
A grocery store sells two brands of a product, the “house” brand and a “name” brand. The manager estimates that if she sells the “house” brand for x dollars and the “name” brand for y dollars, she will be able to sell 81−21x+17y units of the “house” brand and 40+11x−23y units of the “name” brand.
Step 1. Find the revenue function R(x,y).
Step 2. What is the revenue if she sells the “house” brand for $2.30 and the “name” brand for $4.10?
\[R(x,y)=(81-21x+17y)x+(40+11x+23y)y\]
\[R(x,y)=81x-21x^2+17xy+40y+11xy-23y^2\]
\[R(x,y)=81x+40y+28xy+-21x^2+23y^2\]
\[R(2.3,4.1)=116.62\]
A company has a plant in Los Angeles and a plant in Denver. The firm is committed to produce a total of 96 units of a product each week. The total weekly cost is given by \[C(x,y)=\frac{1}{6}x^2+ \frac{1}{6}y^2+7x+25y+700\] where x is the number of units produced in Los Angeles and y is the number of units produced in Denver. How many units should be produced in each plant to minimize the total weekly cost?
Consider x+y=96, then x=96−y
\[C(x,y)= C(96-y,y) =\frac{1}{6}x^2+ \frac{1}{6}y^2+7x+25y+700\]
\[C(x,y)= C(96-y,y) =\frac{1}{6}(96-y)^2+ \frac{1}{6}y^2+7(96-y)+25y+700\]
\[C(x,y)= C(96-y,y) =\frac{1}{3}y^2-14y+2908\]
\[=C_1(y)\]
\[=C'_1(y)=\frac{2}{3}y-14\]
To find minimal value by \[=C'_1(y)=\frac{2}{3}y-14=0\]
\[y=21\]
\[x=96−y=75\]
The company needs to produce 75 units in LA and 21 units in Denver each week in order to meet their production commitment and minimize costs.
Evaluate the double integral on the given region.
\[\iint_R(e^{8x+3y}dA;R:2\le x\le 4 and 2\le y\le 4\]
Write your answer in exact form without decimals.
\[\iint_R(e^{8x+3y}dydx=\int_{2}^{4}(\frac{1}{3}e^{8x+3y})|_{2}^{4}dx\]
\[\iint_R(e^{8x+3y}dydx=\int_{2}^{4}(\frac{1}{3}e^{8x+3y})|_{2}^{4}dx\]
\[=\int_{2}^{4}((\frac{1}{3}e^{8x+12})-(\frac{1}{3}e^{8x+6}))dx\]
\[=\int_{2}^{4}\frac{1}{3}e^{8x+6}(e^6-1)dx\]
\[=\frac{1}{24}e^{8x+6}(e^6-1)|_{2}^{4}\]
\[=\frac{1}{24}e^{32+6}(e^6-1)-\frac{1}{24}e^{16+6}(e^6-1)\]
\[=\frac{1}{24}(e^{6}-1)(e^{38}-e^{22})\]
\[=\frac{1}{24}(e^{44}-e^{38}-e^{28}-e^{22})\]